Discrete mathematics Books

Book SynopsisThis text provides the current state of knowledge on, arguably, one of the most attractive and mysterious mathematical objects: the Monster group. Some 20 experts here share their expertise in this exciting field. Ideal for researchers and graduate students working in Combinatorial Algebra, Group theory and related areas.Trade Review'Describing the Monster group mathematical structures is the culmination of decades of work. Just as the largest Mathieu group framed the 24-dimensional Leech lattice, so also that lattice is the foundation for constructing the Moonshine Module and the Monster algebra, through which the Monster has become central in a theory with deep connections to modern physics. The first part of the book is a collection of five papers on the Monster and other algebraic structures, presented by international leaders in the area providing an outsider with the necessary content and concepts. It presents an account of the current status of the theory and available computational tools for studying the Monster and its algebras. The machinery for developing Majorana theory and axial algebras underpinning the Monster is based on Algebraic Combinatorics, to which the second part of this collection is devoted.' Cheryl Praeger, Emeritus Professor, University of Western Australia''Monstrous Moonshine', an unexpected correspondence involving the largest sporadic simple group, the classical modular function, and conformal field theory, was one of the greatest discoveries of the twentieth century. The modern approach, pioneered by Alexander Ivanov, involves Majorana algebras; the theory is clearly explained here. Among other jewels in the book is a geometric discussion of the Freudenthal - Tits 'magic square', linking the exceptional Lie algebras with the real, complex, quaternion and octonion number fields.' Peter Cameron, University of St AndrewsTable of ContentsPart I. The Monster: 1. Lectures on vertex algebras Atsushi Matsuo; 2. 3-Transposition groups arising in vertex operator algebras Hiroshi Yamauchi; 3. On holomorphic vertex operator algebras of central charge 24 Ching Hung Lam; 4. Maximal 2-local subgroups of the Monster and Baby Monster Ulrich Meierfrankenfeld and Sergey Shpectorov; 5. The future of Majorana theory II Alexander A. Ivanov; Part II. Algebraic Combinatorics: 6. The geometry of Freudenthal-Tits magic square Hendrik Van Maldegham; 7. On generation of polar Grassmanisns Ilaria Cardinali, Lucca Giuzzi and Antonio Pasini; 8. Ovoidal maximal subspaces of polar spaces Antonio Pasini and Hendrik Van Maldegham; 9. On the behaviour of regular unipotent elements from subsystem subgroups of type A_n with special highest weights Tatsiana S. Busel and Irina D. Suprunenko; 10. Some remarks on the parameter c_2 for a distance-regular graph with classical parameters Jack H. Koolen, Jongyook Park and Qianqian Yang; 11. Distance-regular graphs, the subconstituent algebra, and the q-polynomial property Paul Terwilliger; 12. Terwilliger algebras and the Weisfeiler-Leman stabilization Tatsuro Ito; 13. Extended doubling of self-complementary strongly regular graphs and an analogue for digraphs Takuya Ikuta and Akihiro Munemasa; 14. Using GAP package for research in graph theory, design theory and finite geometries Leonard H. Soicher.

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Book SynopsisIntended for first- or second-year graduate students in mathematics, as well as researchers working in algebraic geometry or combinatorics, this text introduces techniques that are essential in several areas of modern mathematics. With numerous exercises and examples, it covers the core notions and applications of equivariant cohomology.Trade Review'This book is a much-needed introduction to a powerful and central tool in algebraic geometry and related subjects. The authors are masters of clarity and rigor. The important theorems and examples are thoroughly explained, and illuminated with well-chosen exercises. This book is an essential companion for anyone wanting to understand group actions in algebraic geometry.' Ravi Vakil, Stanford University'Equivariant Cohomology is a tool from algebraic topology that becomes available when groups act on spaces. In Algebraic geometry, the groups are algebraic groups, including tori, and typical spaces are toric varieties and homogeneous varieties such as Grassmannians and flag varieties. This book introduces and studies equivariant cohomology (actually equivariant Chow groups) from the perspective of algebraic geometry, beginning with the artful replacement of Borel's classifying spaces by Totaro's finite-dimensional approximations. After developing the main properties of equivariant Chow groups, including localization and GKM theory, the authors investigate equivariant Chow groups of toric varieties and flag varieties, and the equivariant classes of Schubert varieties. Reflecting the interests of the authors, special attention is paid to Schubert calculus and the links between degeneracy loci and equivariant cohomology. The text also serves as an introduction to flag varieties, their Schubert varieties, and the calculus of Schubert classes in equivariant cohomology.' Frank Sottile, Texas A&M University'Equivariant Cohomology in Algebraic Geometry by David Anderson and William Fulton offers a comprehensive, accessible exploration of the development, standard examples, and recent contributions in this fascinating field. The authors have successfully struck a balance between rigor and approachability, making it an excellent resource for young researchers in the field. The book's real strength lies in its application to toric varieties and Schubert varieties across various settings, including Grassmannians, flag varieties, degeneracy loci, and extensions to other classical types and Kac–Moody groups. The authors' treatment of Bott-Samelson desingularizations of Schubert varieties is particularly noteworthy, displaying elegance and coherence within the context of the book's material. With over 450 pages of content, Equivariant Cohomology in Algebraic Geometry offers a comprehensive resource for researchers and scholars. It is poised to become a standard reference in the field, leaving a lasting impact on the flourishing area of research for years to come.' Sara Billey, University of WashingtonTable of Contents1. Preview; 2. Defining equivariant cohomology; 3. Basic properties; 4. Grassmannians and flag varieties; 5. Localization I; 6. Conics; 7. Localization II; 8. Toric varieties; 9. Schubert calculus on Grassmannians; 10. Flag varieties and Schubert polynomials; 11. Degeneracy loci; 12. Infinite-dimensional flag varieties; 13. Symplectic flag varieties; 14. Symplectic Schubert polynomials; 15. Homogeneous varieties; 16. The algebra of divided difference operators; 17. Equivariant homology; 18. Bott–_Samelson varieties and Schubert varieties; 19. Structure constants; A. Algebraic topology; B. Specialization in equivariant Borel–_Moore homology; C. Pfaffians and Q-polynomials; D. Conventions for Schubert varieties; E. Characteristic classes and equivariant cohomology; References; Notation index; Subject index.

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Book SynopsisThis concise and self-contained introduction builds up the spectral theory of graphs from scratch, including linear algebra and the theory of polynomials. Covering several types of graphs, it provides the mathematical foundation needed to understand and apply spectral insight to real-world communications systems and complex networks.Table of ContentsSymbols; 1. Introduction; Part I. Spectra of Graphs: 2. Algebraic graph theory; 3. Eigenvalues of the adjacency matrix; 4. Eigenvalues of the Laplacian Q; 5. Effective resistance matrix; 6. Spectra of special types of graphs; 7. Density function of the eigenvalues; 8. Spectra of complex networks; Part II. Eigensystem: 9. Topics in linear algebra; 10. Eigensystem of a matrix; Part III. Polynomials: 11. Polynomials with real coefficients; 12. Orthogonal polynomials; References; Index.

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Book SynopsisThe Traveling Salesman Problem (TSP) is a central topic in discrete mathematics and theoretical computer science. It has been one of the driving forces in combinatorial optimization. The design and analysis of better and better approximation algorithms for the TSP has proved challenging but very fruitful. This is the first book on approximation algorithms for the TSP, featuring a comprehensive collection of all major results and an overview of the most intriguing open problems. Many of the presented results have been discovered only recently, and some are published here for the first time, including better approximation algorithms for the asymmetric TSP and its path version. This book constitutes and advances the state of the art and makes it accessible to a wider audience. Featuring detailed proofs, over 170 exercises, and 100 color figures, this book is an excellent resource for teaching, self-study, and further research.

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Book SynopsisPrimal heuristics guarantee that feasible, high-quality solutions are provided at an early stage of the solving process, and thus are essential to the success of mixed-integer programming (MIP). By helping prove optimality faster, they allow MIP technology to extend to a wide variety of applications in discrete optimization. This first comprehensive guide to the development and use of primal heuristics within MIP technology and solvers is ideal for computational mathematics graduate students and industry practitioners. Through a unified viewpoint, it gives a unique perspective on how state-of-the-art results are integrated within the branch-and-bound approach at the core of the MIP technology. It accomplishes this by highlighting all the required knowledge needed to push the heuristic side of MIP solvers to their limit and pointing out what is left to do to improve them, thus presenting heuristic approaches for MIP as part of the MIP solving process.

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Book SynopsisThis book has enjoyed considerable use and appreciation during its first four editions. With hundreds of students having learned out of early editions, the author continues to find ways to modernize and maintain a unique presentation.What sets the book apart is the excellent writing style, exposition, and unique and thorough sets of exercises. This edition offers a more instructive preface to assist instructors on developing the course they prefer. The prerequisites are more explicit and provide a roadmap for the course. Sample syllabi are included.As would be expected in a fifth edition, the overall content and structure of the book are sound.This new edition offers a more organized treatment of axiomatics. Throughout the book, there is a more careful and detailed treatment of the axioms of set theory. The rules of inference are more carefully elucidated.Additional new features include: An emphasis on the artTrade ReviewThe great strength of the book overall and of the chapters I read is a very accessible writing style, and extremely good exercises. The mix of discussion of advanced topics alongside the presentation of more elementary material is excellent. This is a product of having a highly accomplished and knowledgeable mathematician writing a textbook intended for not-so-advanced students.--David Walnut, George Washington UniversityTable of Contents1. Basic Logic 2. Methods of Proof 3. Set Theory 4. Relations and Functions 5. Group Theory 6. Number Systems 7. More on the Real Number System 8. A Glimpse of Topology 9. Elementary Number Theory 10. Zero-Knowledge Proofs and Cryptography 11. An Example of an Axiomatic Theory

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Book SynopsisThis book is the very first one in the English language entirely dedicated to the Lambert W function, its generalizations, and its applications. One goal is to promote future research on the topic. The book contains all the information one needs when trying to find a result. The most important formulas and results are framed. The Lambert W function is a multi-valued inverse function with plenty of applications in areas like molecular physics, relativity theory, fuel consumption models, plasma physics, analysis of epidemics, bacterial growth models, delay differential equations, fluid mechanics, game theory, statistics, study of magnetic materials, and so on.The first part of the book gives a full treatise of the W function from theoretical point of view.The second part presents generalizations of this function which have been introduced by the need of applications where the classical W function is insufficient.The third part presents a large number of app

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Book SynopsisBasics of Ramsey Theory serves as a gentle introduction to Ramsey theory for students interested in becoming familiar with a dynamic segment of contemporary mathematics that combines ideas from number theory and combinatorics. The core of the of the book consists of discussions and proofs of the results now universally known as Ramsey's theorem, van der Waerden's theorem, Schur's theorem, Rado's theorem, the HalesJewett theorem, and the Happy End Problem of Erdos and Szekeres. The aim is to present these in a manner that will be challenging but enjoyable, and broadly accessible to anyone with a genuine interest in mathematics.Features Suitable for any undergraduate student who has successfully completed the standard calculus sequence of courses and a standard first (or second) year linear algebra course Filled with visual proofs of fundamental theorems Contains numerous exercises (with their solutions) acceTable of Contents1. Introduction: Pioneers and Trailblazers. 1.1. Complete Disorder is Impossible. 1.2 Paul Erdős. 1.3. Frank Plumpton Ramsey. 1.4 Ramsey Theory. 2. Ramsey’s Theorem. 2.1. The Pigeonhole Principle. 2.2. Acquaintances and Strangers. 2.3. Ramsey’s Theorem for Graphs. 2.4. Ramsey’s Theorem: Infinite Case. 2.5. Ramsey’s Theorem: General Case. 2.6. Exercises. 3. van der Waerden’s Theorem. 3.1. Bartel van der Waerden. 3.2. van der Waerden’s Theorem: 3–Term Arithmetic Progressions. 3.3. Proof of van der Waerden’s Theorem. 3.4. van der Waerden’s Theorem: How Far and Where? 3.5. van der Waerden’s Theorem: Some Related Questions. 3.6. Exercises. 4. Schur’s Theorem and Rado’s Theorem. 4.1 Issai Schur. 4.2. Schur’s Theorem. 4.3. Richard Rado. 4.4 Rado’s Theorem. 4.5. Exercises. 5. The Hales–Jewett Theorem. 5.1. Combinatorial Lines. 5.2. Generalized Tic–Tac–Toe Game. 5.3. The Hales–Jewett Theorem. 5.4. Exercises. 6. Happy End Problem. 6.1. The Happy End Problem: Triangles, Quadrilaterals, and Pentagons. 6.2. The Happy End Problem – General Case. 6.3. Erdős–Szekeres’ Upper and Lower Bounds. 6.4. Progress on the Conjecture OF Erdős and Szekeres. 6.5. Exercises. 7. Solutions.

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The Baseball Mysteries: Challenging Puzzles for Logical Detectives is a book of baseball puzzles, logical baseball puzzles. To jump in, all you need is logic and a casual fan's knowledge of the game. The puzzles are solved by reasoning from the rules of the game and a few facts.The logic in the puzzles is like legal reasoning. A solution must argue from evidence (the facts) and law (the rules). Unlike legal arguments, however, a solution must reach an unassailable conclusion.There are many puzzle books. But there's nothing remotely like this book. The puzzles here, while rigorously deductive, are firmly attached to actual events, to struggles that are reported in the papers every day.The puzzles offer a unique and scintillating connection between abstract logic and gritty reality.Actually, this book offers the reader an unlimited number of puzzles. Once you've solved a few of the challenges here, every boxscore you see in the pap

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Book SynopsisIn this book, various numerical methods are discussed in a comprehensive way. It delivers a mixture of theory, examples and MATLAB practicing exercises to help the students in improving their skills. To understand the MATLAB programming in a friendly style, the examples are solved. The MATLAB codes are mentioned in the end of each topic. Throughout the text, a balance between theory, examples and programming is maintained.Key Features Methods are explained with examples and codes System of equations has given full consideration Use of MATLAB is learnt for every method This book is suitable for graduate students in mathematics, computer science and engineering.Table of Contents1. Common Commands Used in Matlab. 2. System of Linear Equations. 3. Polynomial Interpolation. 4. Root Finding Methods. 5. Numerical Integration. 6. Solution of Initial Value Problems. 7. Boundary Value Problems.

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Book SynopsisGraphs & Digraphs, Seventh Edition masterfully employs student-friendly exposition, clear proofs, abundant examples, and numerous exercises to provide an essential understanding of the concepts, theorems, history, and applications of graph theory. This classic text, widely popular among students and instructors alike for decades, is thoroughly streamlined in this new, seventh edition, to present a text consistent with contemporary expectations.Changes and updates to this edition include: A rewrite of four chapters from the ground up Streamlining by over a third for efficient, comprehensive coverage of graph theory Flexible structure with foundational Chapters 16 and customizable topics in Chapters 711 Incorporation of the latest developments in fundamental graph theory Statements of recent groundbreaking discoveries, even if proofs are beyond scope Completely reorganized chapters on traversability, connectiviTable of Contents1 Graphs 1.1 Fundamentals 1.2 Isomorphism 1.3 Families of graphs 1.4 Operations on graphs 1.5 Degree sequences 1.6 Path and cycles 1.7 Connected graphs and distance 1.8 Trees and forests 1.9 Multigraphs and pseudographs 2 Digraphs 2.1 Fundamentals 2.2 Strongly connected digraphs 2.3 Tournaments 2.4 Score sequences 3 Traversability 3.1 Eulerian graphs and digraphs 3.2 Hamiltonian graphs 3.3 Hamiltonian digraphs 3.4 Highly hamiltonian graphs 3.5 Graph powers 4 Connectivity 4.1 Cut-vertices, bridges, and blocks 4.2 Vertex connectivity 4.3 Edge-connectivity 4.4 Menger's theorem 5 Planarity 5.1 Euler's formula 5.2 Characterizations of planarity 5.3 Hamiltonian planar graphs 5.4 The crossing number of a graph 6 Coloring 6.1 Vertex coloring 6.2 Edge coloring 6.3 Critical and perfect graphs 6.4 Maps and planar graphs 7 Flows 7.1 Networks 7.2 Max-flow min-cut theorem 7.3 Menger's theorems for digraphs 7.4 A connection to coloring 8 Factors and covers 8.1 Matchings and 1-factors 8.2 Independence and covers 8.3 Domination 8.4 Factorizations and decompositions 8.5 Labelings of graphs 9 Extremal graph theory 9.1 Avoiding a complete graph 9.2 Containing cycles and trees 9.3 Ramsey theory 9.4 Cages and Moore graphs 10 Embeddings 10.1 The genus of a graph 10.2 2-Cell embeddings of graphs 10.3 The maximum genus of a graph 10.4 The graph minor theorem 11 Graphs and algebra 11.1 Graphs and matrices 11.2 The automorphism group 11.3 Cayley color graphs 11.4 The reconstruction problem

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Book SynopsisUpdated to reflect current research and extended to cover more advanced topics as well as the basics, Algebraic Number Theory and Fermatâs Last Theorem, Fifth Edition introduces fundamental ideas of algebraic numbers and explores one of the most intriguing stories in the history of mathematicsâthe quest for a proof of Fermatâs Last Theorem. The authors use this celebrated theorem to motivate a general study of the theory of algebraic numbers, initially from a relatively concrete point of view. Students will see how Wilesâs proof of Fermatâs Last Theorem opened many new areas for future work. New to the Fifth Edition Pell's Equation x^2-dy^2=1: all solutions can be obtained from a single `fundamental' solution, which can be found using continued fractions. Galois theory of number field extensions, relating the field structure to that of the group of automorphisms. More material on cyclotomic fields, and some results on cubic fields

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Book SynopsisDesigned for advanced undergraduate and beginning graduate students in linear or abstract algebra, Advanced Linear Algebra covers theoretical aspects of the subject, along with examples, computations, and proofs. It explores a variety of advanced topics in linear algebra that highlight the rich interconnections of the subject to geometry, algebra, analysis, combinatorics, numerical computation, and many other areas of mathematics.The author begins with chapters introducing basic notation for vector spaces, permutations, polynomials, and other algebraic structures. The following chapters are designed to be mostly independent of each other so that readers with different interests can jump directly to the topic they want. This is an unusual organization compared to many abstract algebra textbooks, which require readers to follow the order of chapters.Each chapter consists of a mathematical vignette devoted to the development of one specific topic.

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Book SynopsisIn applications of stochastic calculus, there are phenomena that cannot be analyzed through the classical Ità theory. It is necessary, therefore, to have a theory based on stochastic integration with respect to these situations.Theory of Stochastic Integrals aims to provide the answer to this problem by introducing readers to the study of some interpretations of stochastic integrals with respect to stochastic processes that are not necessarily semimartingales, such as Volterra Gaussian processes, or processes with bounded p-variation among which we can mention fractional Brownian motion and Riemann-Liouville fractional process.Features Self-contained treatment of the topic Suitable as a teaching or research tool for those interested in stochastic analysis and its applications Includes original results.

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Book SynopsisThis book is a concise, selfâcontained treatment of the finite element method and all the computational techniques needed for its efficient use and practical implementation. This book describes the process of transforming the physical problem into a mathematical model, the reduction of the mathematical model to a numerically solvable computational form, and many practical engineering analysis solution techniques applied in various industries.The first edition of this book was published in 2004, two decades ago. Since then, finite element analysis (FEA) has become a fundamental component of product development software tools (CAD, CAE, CAM) used in many industrial fields of engineering, particularly in mechanical and aerospace engineering. It has also become a popular text in computational science in engineering (CSE) and applied mathematics courses in academia, one of the reasons for the new edition.This new edition presents finite element solutions to advanced industr

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Book SynopsisRichard Stanley's two-volume basic introduction to enumerative combinatorics has become the standard guide to the topic for students and experts alike. This thoroughly revised second edition of Volume 1 includes ten new sections and more than 300 new exercises, most with solutions, reflecting numerous new developments since the publication of the first edition in 1986. The author brings the coverage up to date and includes a wide variety of additional applications and examples, as well as updated and expanded chapter bibliographies. Many of the less difficult new exercises have no solutions so that they can more easily be assigned to students. The material on P-partitions has been rearranged and generalized; the treatment of permutation statistics has been greatly enlarged; and there are also new sections on q-analogues of permutations, hyperplane arrangements, the cd-index, promotion and evacuation and differential posets.Trade Review'… sure to become a standard as an introductory graduate text in combinatorics.' Bulletin of the American Mathematical Society'… will engage from start to finish the attention of any mathematician who will open it at page one.' Gian-Carlo RotaTable of Contents1. What is enumerative combinatorics?; 2. Sieve methods; 3. Partially ordered sets; 4. Rational generating functions.

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Book SynopsisThe projective and polar geometries that arise from a vector space over a finite field are particularly useful in the construction of combinatorial objects, such as latin squares, designs, codes and graphs. This book provides an introduction to these geometries and their many applications to other areas of combinatorics. Coverage includes a detailed treatment of the forbidden subgraph problem from a geometrical point of view, and a chapter on maximum distance separable codes, which includes a proof that such codes over prime fields are short. The author also provides more than 100 exercises (complete with detailed solutions), which show the diversity of applications of finite fields and their geometries. Finite Geometry and Combinatorial Applications is ideal for anyone, from a third-year undergraduate to a researcher, who wishes to familiarise themselves with and gain an appreciation of finite geometry.Table of Contents1. Fields; 2. Vector spaces; 3. Forms; 4. Geometries; 5. Combinatorial applications; 6. The forbidden subgraph problem; 7. MDS codes; Appendix A. Solutions to the exercises; Appendix B. Additional proofs; Appendix C. Notes and references; References; Index.

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Book SynopsisFrom social networks such as Facebook, the World Wide Web and the Internet, to the complex interactions between proteins in the cells of our bodies, we constantly face the challenge of understanding the structure and development of networks. The theory of random graphs provides a framework for this understanding, and in this book the authors give a gentle introduction to the basic tools for understanding and applying the theory. Part I includes sufficient material, including exercises, for a one semester course at the advanced undergraduate or beginning graduate level. The reader is then well prepared for the more advanced topics in Parts II and III. A final part provides a quick introduction to the background material needed. All those interested in discrete mathematics, computer science or applied probability and their applications will find this an ideal introduction to the subject.Trade Review'This is a well-planned book that is true to its title in that it is indeed accessible for anyone with just an undergraduate student's knowledge of enumerative combinatorics and probability.' Miklós Bóna, MAA ReviewsTable of ContentsPreface; Part I. Basic Models: 1. Random graphs; 2. Evolution; 3. Vertex degrees; 4. Connectivity; 5. Small subgraphs; 6. Spanning subgraphs; 7. Extreme characteristics; 8. Extremal properties; Part II. Basic Model Extensions: 9. Inhomogeneous graphs; 10. Fixed degree sequence; 11. Intersection graphs; 12. Digraphs; 13. Hypergraphs; Part III. Other Models: 14. Trees; 15. Mappings; 16. k-out; 17. Real-world networks; 18. Weighted graphs; 19. Brief notes on uncovered topics; Part IV. Tools and Methods: 20. Moments; 21. Inequalities; 22. Differential equations method; 23. Branching processes; 24. Entropy; References; Author index; Main index.

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Book SynopsisCatalan numbers are probably the most ubiquitous sequence of numbers in mathematics. This book gives for the first time a comprehensive collection of their properties and applications to combinatorics, algebra, analysis, number theory, probability theory, geometry, topology, and other areas. Following an introduction to the basic properties of Catalan numbers, the book presents 214 different kinds of objects counted by them in the form of exercises with solutions. The reader can try solving the exercises or simply browse through them. Some 68 additional exercises with prescribed difficulty levels present various properties of Catalan numbers and related numbers, such as Fuss-Catalan numbers, Motzkin numbers, SchrÃder numbers, Narayana numbers, super Catalan numbers, q-Catalan numbers and (q,t)-Catalan numbers. The book ends with a history of Catalan numbers by Igor Pak and a glossary of key terms. Whether your interest in mathematics is recreation or research, you will find plenty of fTable of Contents1. Basic properties; 2. Bijective exercises; 3. Bijective solutions; 4. Additional problems; 5. Solutions to additional problems.

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Book SynopsisRichard Stanley's two-volume basic introduction to enumerative combinatorics has become the standard guide to the topic for students and experts alike. This thoroughly revised second edition of Volume 1 includes more than 300 new exercises, many with solutions, updated and expanded chapter bibliographies and substantial new material on permutation statistics.Trade Review'… sure to become a standard as an introductory graduate text in combinatorics.' Bulletin of the American Mathematical Society'… will engage from start to finish the attention of any mathematician who will open it at page one.' Gian-Carlo RotaTable of Contents1. What is enumerative combinatorics?; 2. Sieve methods; 3. Partially ordered sets; 4. Rational generating functions.

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Book SynopsisRandomized algorithms have become a central part of the algorithms curriculum, based on their increasingly widespread use in modern applications. This book presents a coherent and unified treatment of probabilistic techniques for obtaining high probability estimates on the performance of randomized algorithms. It covers the basic toolkit from the ChernoffâHoeffding bounds to more sophisticated techniques like martingales and isoperimetric inequalities, as well as some recent developments like Talagrand's inequality, transportation cost inequalities and log-Sobolev inequalities. Along the way, variations on the basic theme are examined, such as ChernoffâHoeffding bounds in dependent settings. The authors emphasise comparative study of the different methods, highlighting respective strengths and weaknesses in concrete example applications. The exposition is tailored to discrete settings sufficient for the analysis of algorithms, avoiding unnecessary measure-theoretic details, thus makingTrade ReviewReview of the hardback: 'It is beautifully written, contains all the major concentration results, and is a must to have on your desk.' Richard LiptonReview of the hardback: 'Concentration bounds are at the core of probabilistic analysis of algorithms. This excellent text provides a comprehensive treatment of this important subject, ranging from the very basic to the more advanced tools, including some recent developments in this area. The presentation is clear and includes numerous examples, demonstrating applications of the bounds in analysis of algorithms. This book is a valuable resource for both researchers and students in the field.' Eli Upfal, Brown UniversityReview of the hardback: 'Concentration inequalities are an essential tool for the analysis of algorithms in any probabilistic setting. There have been many recent developments on this subject, and this excellent text brings them together in a highly accessible form.' Alan Frieze, Carnegie Mellon UniversityReview of the hardback: 'The book does a superb job of describing a collection of powerful methodologies in a unified manner; what is even more striking is that basic combinatorial and probabilistic language is used in bringing out the power of such approaches. To summarize, the book has done a great job of synthesizing diverse and important material in a very accessible manner. Any student, researcher, or practitioner of computer science, electrical engineering, mathematics, operations research, and related fields, could benefit from this wonderful book. The book would also make for fruitful classes at the undergraduate and graduate levels. I highly recommend it.' Aravind Srinivasan, SIGACT NewsReview of the hardback: '… the strength of this book is that it is appropriate for both the beginner as well as the experienced researcher in the field of randomized algorithms … The exposition style […] combines informal discussion with formal definitions and proofs, giving first the intuition and motivation for the probabalistic technique at hand. … I highly recommend this book both as an advanced as well as an introductory textbook, which can also serve the needs of an experienced researcher in algorithmics.' Yannis C. Stamatiou, Mathematical ReviewsReviews of the hardback: 'This timely book brings together in a comprehensive and accessible form a sophisticated toolkit of powerful techniques for the analysis of randomized algorithms, illustrating their use with a wide array of insightful examples. This book is an invaluable resource for people venturing into this exciting field of contemporary computer science research.' Prabhakar Ragahavan, Yahoo ResearchTable of Contents1. Chernoff–Hoeffding bounds; 2. Applying the CH-bounds; 3. CH-bounds with dependencies; 4. Interlude: probabilistic recurrences; 5. Martingales and the MOBD; 6. The MOBD in action; 7. Averaged bounded difference; 8. The method of bounded variances; 9. Interlude: the infamous upper tail; 10. Isoperimetric inequalities and concentration; 11. Talagrand inequality; 12. Transportation cost and concentration; 13. Transportation cost and Talagrand's inequality; 14. Log–Sobolev inequalities; Appendix A. Summary of the most useful bounds.

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Book SynopsisA concise yet rigorous introduction to logic and discrete mathematics. This book features a unique combination of comprehensive coverage of logic with a solid exposition of the most important fields of discrete mathematics, presenting material that has been tested and refined by the authors in university courses taught over more than a decade. The chapters on logic - propositional and first-order - provide a robust toolkit for logical reasoning, emphasizing the conceptual understanding of the language and the semantics of classical logic as well as practical applications through the easy to understand and use deductive systems of Semantic Tableaux and Resolution. The chapters on set theory, number theory, combinatorics and graph theory combine the necessary minimum of theory with numerous examples and selected applications. Written in a clear and reader-friendly style, each section ends with an extensive set of exercises, most of them provided with complete soluTrade Review"This is a very well-written brief introduction to discrete mathematics that emphasizes logic and set theory and has shorter sections on number theory, combinatorics, and graph theory." (MAA Reviews, 4 January 2016)Table of ContentsList of Boxes xiii Preface xvii Acknowledgements xxi About the Companion Website xxiii 1. Preliminaries 1 1.1 Sets 2 1.1.1 Exercises 7 1.2 Basics of logical connectives and expressions 9 1.2.1 Propositions, logical connectives, truth tables, tautologies 9 1.2.2 Individual variables and quantifiers 12 1.2.3 Exercises 15 1.3 Mathematical induction 17 1.3.1 Exercises 18 2. Sets, Relations, Orders 20 2.1 Set inclusions and equalities 21 2.1.1 Properties of the set theoretic operations 22 2.1.2 Exercises 26 2.2 Functions 28 2.2.1 Functions and their inverses 28 2.2.2 Composition of mappings 31 2.2.3 Exercises 33 2.3 Binary relations and operations on them 35 2.3.1 Binary relations 35 2.3.2 Matrix and graphical representations of relations on finite sets 38 2.3.3 Boolean operations on binary relations 39 2.3.4 Inverse and composition of relations 41 2.3.5 Exercises 42 2.4 Special binary relations 45 2.4.1 Properties of binary relations 45 2.4.2 Functions as relations 47 2.4.3 Reflexive, symmetric and transitive closures of a relation 47 2.4.4 Exercises 49 2.5 Equivalence relations and partitions 51 2.5.1 Equivalence relations 51 2.5.2 Quotient sets and partitions 53 2.5.3 The kernel equivalence of a mapping 56 2.5.4 Exercises 57 2.6 Ordered sets 59 2.6.1 Pre-orders and partial orders 59 2.6.2 Graphical representing posets: Hasse diagrams 61 2.6.3 Lower and upper bounds. Minimal and maximal elements 63 2.6.4 Well-ordered sets 65 2.6.5 Exercises 67 2.7 An introduction to cardinality 69 2.7.1 Equinumerosity and cardinality 69 2.7.2 Exercises 73 2.8 Isomorphisms of ordered sets. Ordinal numbers 75 2.8.1 Exercises 79 2.9 Application: relational databases 80 2.9.1 Exercises 86 3. Propositional Logic 89 3.1 Propositions, logical connectives, truth tables, tautologies 90 3.1.1 Propositions and propositional connectives. Truth tables 90 3.1.2 Some remarks on the meaning of the connectives 90 3.1.3 Propositional formulae 91 3.1.4 Construction and parsing tree of a propositional formula 92 3.1.5 Truth tables of propositional formulae 93 3.1.6 Tautologies 95 3.1.7 A better idea: search for a falsifying truth assignment 96 3.1.8 Exercises 97 3.2 Propositional logical consequence. Valid and invalid propositional inferences 101 3.2.1 Propositional logical consequence 101 3.2.2 Logically sound rules of propositional inference. Logically correct propositional arguments 104 3.2.3 Fallacies of the implication 106 3.2.4 Exercises 107 3.3 The concept and use of deductive systems 109 3.4 Semantic tableaux 113 3.4.1 Exercises 117 3.5 Logical equivalences. Negating propositional formulae 121 3.5.1 Logically equivalent propositional formulae 121 3.5.2 Some important equivalences 123 3.5.3 Exercises 124 3.6 Normal forms. Propositional resolution 126 3.6.1 Conjunctive and disjunctive normal forms of propositional formulae 126 3.6.2 Clausal form. Clausal resolution 129 3.6.3 Resolution-based derivations 130 3.6.4 Optimizing the method of resolution 131 3.6.5 Exercises 132 4. First-Order Logic 135 4.1 Basic concepts of first-order logic 136 4.1.1 First-order structures 136 4.1.2 First-order languages 138 4.1.3 Terms and formulae 139 4.1.4 The semantics of first-order logic: an informal outline 143 4.1.5 Translating first-order formulae to natural language 146 4.1.6 Exercises 147 4.2 The formal semantics of first–order logic 152 4.2.1 Interpretations 152 4.2.2 Variable assignment and term evaluation 153 4.2.3 Truth evaluation games 156 4.2.4 Exercises 159 4.3 The language of first-order logic: a deeper look 161 4.3.1 Translations from natural language into first-order languages 161 4.3.2 Restricted quantification 163 4.3.3 Free and bound variables. Scope of a quantifier 164 4.3.4 Renaming of a bound variable in a formula. Clean formulae 165 4.3.5 Substitution of a term for a variable in a formula. Capture of a variable 166 4.3.6 Exercises 167 4.4 Truth, logical validity, equivalence and consequence in first-order logic 171 4.4.1 More on truth of sentences in structures. Models and countermodels 171 4.4.2 Satisfiability and validity of first-order formulae 172 4.4.3 Logical equivalence in first-order logic 173 4.4.4 Some logical equivalences involving quantifiers 174 4.4.5 Negating first-order formulae 175 4.4.6 Logical consequence in first-order logic 176 4.4.7 Exercises 180 4.5 Semantic tableaux for first-order logic 185 4.5.1 Some derivations using first-order semantic tableau 186 4.5.2 Semantic tableaux for first-order logic with equality 189 4.5.3 Discussion on the quantifier rules and on termination of semantic tableaux 189 4.5.4 Exercises 191 4.6 Prenex and clausal normal forms 195 4.6.1 Prenex normal forms 195 4.6.2 Skolemization 197 4.6.3 Clausal forms 198 4.6.4 Exercises 199 4.7 Resolution in first-order logic 201 4.7.1 Propositional resolution rule in first-order logic 201 4.7.2 Substitutions of terms for variables revisited 201 4.7.3 Unification of terms 202 4.7.4 Resolution with unification in first-order logic 204 4.7.5 Examples of resolution-based derivations 205 4.7.6 Resolution for first-order logic with equality 207 4.7.7 Optimizations of the resolution method for first-order logic 207 4.7.8 Exercises 207 4.8 Applications of first-order logic to mathematical reasoning and proofs 211 4.8.1 Proof strategies: direct and indirect proofs 211 4.8.2 Tactics for logical reasoning 215 4.8.3 Exercises 216 5. Number Theory 219 5.1 The principle of mathematical induction revisited 220 5.1.1 Exercises 222 5.2 Divisibility 224 5.2.1 Basic properties of divisibility 224 5.2.2 Division with a remainder 224 5.2.3 Greatest common divisor 225 5.2.4 Exercises 227 5.3 Computing greatest common divisors. Least common multiples 230 5.3.1 Euclid’s algorithm for computing greatest common divisors 230 5.3.2 Least common multiple 232 5.3.3 Exercises 233 5.4 Prime numbers. The fundamental theorem of arithmetic 236 5.4.1 Relatively prime numbers 236 5.4.2 Prime numbers 237 5.4.3 The fundamental theorem of arithmetic 238 5.4.4 On the distribution of prime numbers 239 5.4.5 Exercises 240 5.5 Congruence relations 243 5.5.1 Exercises 246 5.6 Equivalence classes and residue systems modulo n 248 5.6.1 Equivalence relations and partitions 248 5.6.2 Equivalence classes modulo n. Modular arithmetic 249 5.6.3 Residue systems 250 5.6.4 Multiplicative inverses in ℤn 251 5.6.5 Exercises 251 5.7 Linear Diophantine equations and linear congruences 253 5.7.1 Linear Diophantine equations 253 5.7.2 Linear congruences 254 5.7.3 Exercises 256 5.8 Chinese remainder theorem 257 5.8.1 Exercises 259 5.9 Euler’s function. Theorems of Euler and Fermat 261 5.9.1 Theorems of Euler and Fermat 262 5.9.2 Exercises 264 5.10 Wilson’s theorem. Order of an integer 266 5.10.1 Wilson’s theorem 266 5.10.2 Order of an integer 266 5.10.3 Exercises 267 5.11 Application: public key cryptography 269 5.11.1 About cryptography 269 5.11.2 The idea of public key cryptography 269 5.11.3 The method RSA 270 5.11.4 Exercises 271 6. Combinatorics 274 6.1 Two basic counting principles 275 6.1.1 Exercises 281 6.2 Combinations. The binomial theorem 284 6.2.1 Counting sheep and combinations 284 6.2.2 Some important properties 286 6.2.3 Pascal’s triangle 287 6.2.4 The binomial theorem 287 6.2.5 Exercises 289 6.3 The principle of inclusion–exclusion 293 6.3.1 Exercises 296 6.4 The Pigeonhole Principle 299 6.4.3 Exercises 302 6.5 Generalized permutations, distributions and the multinomial theorem 304 6.5.1 Arranging nondistinct objects 304 6.5.2 Distributions 306 6.5.3 The multinomial theorem 308 6.5.4 Summary 310 6.5.5 Exercises 311 6.6 Selections and arrangements with repetition; distributions of identical objects 312 6.6.1 Selections with repetition 312 6.6.2 Distributions of identical objects 314 6.6.3 Arrangements with repetition 315 6.6.4 Summary 316 6.6.5 Exercises 316 6.7 Recurrence relations and their solution 318 6.7.1 Recurrence relations. Fibonacci numbers 318 6.7.2 Catalan numbers 319 6.7.3 Solving homogeneous linear recurrence relations 322 6.7.4 Exercises 327 6.8 Generating functions 329 6.8.1 Introducing generating functions 329 6.8.2 Computing coefficients of generating functions 332 6.8.3 Exercises 335 6.9 Recurrence relations and generating functions 337 6.9.1 Exercises 341 6.10 Application: classical discrete probability 343 6.10.1 Common sense probability 343 6.10.2 Sample spaces 343 6.10.3 Discrete probability 345 6.10.4 Properties of probability measures 346 6.10.5 Conditional probability and independent events 348 6.10.6 Exercises 352 7. Graph Theory 356 7.1 Introduction to graphs and digraphs 357 7.1.1 Graphs 357 7.1.2 Digraphs 364 7.1.3 Exercises 367 7.2 Incidence and adjacency matrices 370 7.2.1 Exercises 374 7.3 Weighted graphs and path algorithms 377 7.3.1 Dijkstra’s algorithm 378 7.3.2 The Floyd–Warshall algorithm 381 7.3.3 Exercises 383 7.4 Trees 385 7.4.1 Undirected trees 385 7.4.2 Computing spanning trees: Kruskal’s algorithm 388 7.4.3 Rooted trees 390 7.4.4 Traversing rooted trees 392 7.4.5 Exercises 393 7.5 Eulerian graphs and Hamiltonian graphs 395 7.5.1 Eulerian graphs and digraphs 396 7.5.2 Hamiltonian graphs and digraphs 398 7.5.3 Exercises 400 7.6 Planar graphs 404 7.6.1 Exercises 408 7.7 Graph colourings 411 7.7.1 Colourings 411 7.7.2 The four- and five-colour theorems 413 7.7.3 Exercises 414 Index 419

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Book SynopsisSolutions manual to accompanyTable of ContentsPreface vii About the Companion Website ix 1. Preliminaries 1 2. Sets, Relations, Orders 5 3. Propositional Logic 29 4. First-Order Logic 57 5. Number Theory 99 6. Combinatorics 130 7. Graph Theory 159

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Book SynopsisThis set includes Finite Mathematics: Models and Applications & Solutions Manual to accompany Finite Mathematics: Models and Applications Finite Mathematics: Models and Applications emphasizes cross-disciplinary applications that relate mathematics to everyday life. The book provides a unique combination of practical mathematical applications to illustrate the wide use of mathematics in fields ranging from business, economics, finance, management, operations research, and the life and social sciences. The book features coverage including: Algebra Skills; Mathematics of Finance; Matrix Algebra; Geometric Solutions; Simplex Methods; Application Models; Set and Probability Relationships; Random Variables and Probability Distributions; Markov Chains; Mathematical Statistics; Enrichment in Finite MathematicsTable of ContentsPreface ix About the Authors xi 1 Linear Equations and Mathematical Concepts 1 1.1 Solving Linear Equations 2 1.2 Equations of Lines and Their Graphs 7 1.3 Solving Systems of Linear Equations 15 1.4 The Numbers 𝜋 and e 21 1.5 Exponential and Logarithmic Functions 24 1.6 Variation 32 1.7 Unit Conversions and Dimensional Analysis 38 2 Mathematics of Finance 47 2.1 Simple and Compound Interest 47 2.2 Ordinary Annuity 55 2.3 Amortization 59 2.4 Arithmetic and Geometric Sequences 63 3 Matrix Algebra 71 3.1 Matrices 72 3.2 Matrix Notation, Arithmetic, and Augmented Matrices 78 3.3 Gauss–Jordan Elimination 89 3.4 Matrix Inversion and Input–Output Analysis 100 4 Linear Programming – Geometric Solutions 116 Introduction 116 4.1 Graphing Linear Inequalities 117 4.2 Graphing Systems of Linear Inequalities 121 4.3 Geometric Solutions to Linear Programs 125 5 Linear Programming – Simplex Method 136 5.1 The Standard Maximization Problem (SMP) 137 5.2 Tableaus and Pivot Operations 142 5.3 Optimal Solutions and the Simplex Method 149 5.4 Dual Programs 161 5.5 Non-SMP Linear Programs 167 6 Linear Programming – Application Models 182 7 Set and Probability Relationships 203 7.1 Sets 204 7.2 Venn Diagrams 210 7.3 Tree Diagrams 216 7.4 Combinatorics 221 7.5 Mathematical Probability 231 7.6 Bayes’ Rule and Decision Trees 245 8 Random Variables and Probability Distributions 259 8.1 Random Variables 259 8.2 Bernoulli Trials and the Binomial Distribution 265 8.3 The Hypergeometric Distribution 273 8.4 The Poisson Distribution 279 9 Markov Chains 285 9.1 Transition Matrices and Diagrams 286 9.2 Transitions 291 9.3 Regular Markov Chains 295 9.4 Absorbing Markov Chains 304 10 Mathematical Statistics 314 10.1 Graphical Descriptions of Data 315 10.2 Measures of Central Tendency and Dispersion 323 10.3 The Uniform Distribution 331 10.4 The Normal Distribution 334 10.5 Normal Distribution Applications 348 10.6 Developing and Conducting a Survey 363 11 Enrichment in Finite Mathematics 371 11.1 Game Theory 372 11.2 Applications in Finance and Economics 385 11.3 Applications in Social and Life Sciences 394 11.4 Monte Carlo Method 403 11.5 Dynamic Programming 422 Answers to Odd Numbered Exercises 439 Using Technology 502 Glossary 506 Index 513

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Book SynopsisA PRACTICAL GUIDE TO OPTIMIZATION PROBLEMS WITH DISCRETE OR INTEGER VARIABLES, REVISED AND UPDATED The revised second edition of Integer Programming explains in clear and simple terms how to construct custom-made algorithms or use existing commercial software to obtain optimal or near-optimal solutions for a variety of real-world problems. The second edition also includes information on the remarkable progress in the development of mixed integer programming solvers in the 22 years since the first edition of the book appeared. The updated text includes information on the most recent developments in the field such as the much improved preprocessing/presolving and the many new ideas for primal heuristics included in the solvers. The result has been a speed-up of several orders of magnitude. The other major change reflected in the text is the widespread use of decomposition algorithms, in particular column generation (branch-(cut)-and-price) and Benders' decompositiTable of ContentsPreface to the Second Edition xii Preface to the First Edition xiii Abbreviations and Notation xvii About the Companion Website xix 1 Formulations 1 1.1 Introduction 1 1.2 What Is an Integer Program? 3 1.3 Formulating IPs and BIPs 5 1.4 The Combinatorial Explosion 8 1.5 Mixed Integer Formulations 9 1.6 Alternative Formulations 12 1.7 Good and Ideal Formulations 15 1.8 Notes 18 1.9 Exercises 19 2 Optimality, Relaxation, and Bounds 25 2.1 Optimality and Relaxation 25 2.2 Linear Programming Relaxations 27 2.3 Combinatorial Relaxations 28 2.4 Lagrangian Relaxation 29 2.5 Duality 30 2.6 Linear Programming and Polyhedra 32 2.7 Primal Bounds: Greedy and Local Search 34 2.8 Notes 38 2.9 Exercises 38 3 Well-Solved Problems 43 3.1 Properties of Easy Problems 43 3.2 IPs with Totally Unimodular Matrices 44 3.3 Minimum Cost Network Flows 46 3.4 Special Minimum Cost Flows 48 3.4.1 Shortest Path 48 3.4.2 Maximum s − t Flow 49 3.5 Optimal Trees 50 3.6 Submodularity and Matroids 54 3.7 Two Harder Network Flow Problems 57 3.8 Notes 59 3.9 Exercises 60 4 Matchings and Assignments 63 4.1 Augmenting Paths and Optimality 63 4.2 Bipartite Maximum Cardinality Matching 65 4.3 The Assignment Problem 67 4.4 Matchings in Nonbipartite Graphs 73 4.5 Notes 74 4.6 Exercises 75 5 Dynamic Programming 79 5.1 Some Motivation: Shortest Paths 79 5.2 Uncapacitated Lot-Sizing 80 5.3 An Optimal Subtree of a Tree 83 5.4 Knapsack Problems 84 5.4.1 0–1 Knapsack Problems 85 5.4.2 Integer Knapsack Problems 86 5.5 The Cutting Stock Problem 89 5.6 Notes 91 5.7 Exercises 92 6 Complexity and Problem Reductions 95 6.1 Complexity 95 6.2 Decision Problems, and Classes NP and P 96 6.3 Polynomial Reduction and the Class NPC 98 6.4 Consequences of P =NP orP ≠NP 103 6.5 Optimization and Separation 104 6.6 The Complexity of Extended Formulations 105 6.7 Worst-Case Analysis of Heuristics 106 6.8 Notes 109 6.9 Exercises 110 7 Branch and Bound 113 7.1 Divide and Conquer 113 7.2 Implicit Enumeration 114 7.3 Branch and Bound: an Example 116 7.4 LP-Based Branch and Bound 120 7.5 Using a Branch-and-Bound/Cut System 123 7.6 Preprocessing or Presolve 129 7.7 Notes 134 7.8 Exercises 135 8 Cutting Plane Algorithms 139 8.1 Introduction 139 8.2 Some Simple Valid Inequalities 140 8.3 Valid Inequalities 143 8.4 A Priori Addition of Constraints 147 8.5 Automatic Reformulation or Cutting Plane Algorithms 149 8.6 Gomory’s Fractional Cutting Plane Algorithm 150 8.7 Mixed Integer Cuts 153 8.7.1 The Basic Mixed Integer Inequality 153 8.7.2 The Mixed Integer Rounding (MIR) Inequality 155 8.7.3 The Gomory Mixed Integer Cut 155 8.7.4 Split Cuts 156 8.8 Disjunctive Inequalities and Lift-and-Project 158 8.9 Notes 161 8.10 Exercises 162 9 Strong Valid Inequalities 167 9.1 Introduction 167 9.2 Strong Inequalities 168 9.3 0–1 Knapsack Inequalities 175 9.3.1 Cover Inequalities 175 9.3.2 Strengthening Cover Inequalities 176 9.3.3 Separation for Cover Inequalities 178 9.4 Mixed 0–1 Inequalities 179 9.4.1 Flow Cover Inequalities 179 9.4.2 Separation for Flow Cover Inequalities 181 9.5 The Optimal Subtour Problem 183 9.5.1 Separation for Generalized Subtour Constraints 183 9.6 Branch-and-Cut 186 9.7 Notes 189 9.8 Exercises 190 10 Lagrangian Duality 195 10.1 Lagrangian Relaxation 195 10.2 The Strength of the Lagrangian Dual 200 10.3 Solving the Lagrangian Dual 202 10.4 Lagrangian Heuristics 205 10.5 Choosing a Lagrangian Dual 207 10.6 Notes 209 10.7 Exercises 210 11 Column (and Row) Generation Algorithms 213 11.1 Introduction 213 11.2 The Dantzig–Wolfe Reformulation of an IP 215 11.3 Solving the LP Master Problem: Column Generation 216 11.4 Solving the Master Problem: Branch-and-Price 219 11.5 Problem Variants 222 11.5.1 Handling Multiple Subproblems 222 11.5.2 Partitioning/Packing Problems with Additional Variables 223 11.5.3 Partitioning/Packing Problems with Identical Subsets 224 11.6 Computational Issues 225 11.7 Branch-Cut-and-Price: An Example 226 11.7.1 A Capacitated Vehicle Routing Problem 226 11.7.2 Solving the Subproblems 229 11.7.3 The Load Formulation 230 11.8 Notes 231 11.9 Exercises 232 12 Benders’ Algorithm 235 12.1 Introduction 235 12.2 Benders’ Reformulation 236 12.3 Benders’ with Multiple Subproblems 240 12.4 Solving the Linear Programming Subproblems 242 12.5 Integer Subproblems: Basic Algorithms 244 12.5.1 Branching in the (x, 𝜂, y)-Space 244 12.5.2 Branching in (x, 𝜂)-Space and “No-Good” Cuts 246 12.6 Notes 247 12.7 Exercises 248 13 Primal Heuristics 251 13.1 Introduction 251 13.2 Greedy and Local Search Revisited 252 13.3 Improved Local Search Heuristics 255 13.3.1 Tabu Search 255 13.3.2 Simulated Annealing 256 13.3.3 Genetic Algorithms 257 13.4 Heuristics Inside MIP Solvers 259 13.4.1 Construction Heuristics 259 13.4.2 Improvement Heuristics 261 13.5 User-Defined MIP heuristics 262 13.6 Notes 265 13.7 Exercises 266 14 From Theory to Solutions 269 14.1 Introduction 269 14.2 Software for Solving Integer Programs 269 14.3 How Do We Find an Improved Formulation? 272 14.4 Multi-item Single Machine Lot-Sizing 277 14.5 A Multiplexer Assignment Problem 282 14.6 Integer Programming and Machine Learning 285 14.7 Notes 287 14.8 Exercises 287 References 291 Index 311

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Book SynopsisAutomata and Computability is a class-tested textbook which provides a comprehensive and accessible introduction to the theory of automata and computation. The author uses illustrations, engaging examples, and historical remarks to make the material interesting and relevant for students. It incorporates modern/handy ideas, such as derivative-based parsing and a Lambda reducer showing the universality of Lambda calculus. The book also shows how to sculpt automata by making the regular language conversion pipeline available through a simple command interface. A Jupyter notebook will accompany the book to feature code, YouTube videos, and other supplements to assist instructors and studentsFeatures Uses illustrations, engaging examples, and historical remarks to make the material accessible Incorporates modern/handy ideas, such as derivative-based parsing and a Lambda reducer showing the universality of Lambda Trade Review"I have taught formal languages and automata theory for decades, and I have seen many, perhaps most, students struggle with the material because it is so abstract. I've often thought that computer science students would learn it better by programming it. Indeed, that's how I really learned these topics -- by implementing constructions directly in practical compiler generation and formal verification tools to do my research. Prof. Gopalakrishnan's approach is to have students learn by doing, while still going into greater depth than some purely pencil-and-paper courses." -Prof. David L. Dill, Donald E. Knuth Professor, Emeritus, in the School of Engineering, Stanford University "It is probably a safe assumption to make these days that many, if not most, computer science undergraduates have had programming experience, but few of them know the language of mathematics. Professor Gopalakrishnan’s book builds on the student’s experience in programming and animates the theory of automata, formal languages, and computability with actual programs which the student can easily modify and play with. Doing is the best way of learning. This book should enable the typical computer science student to acquire a more visceral, and therefore in the long run more useful, understanding of the theory." -Dr. Ching-Tsun Chou, Silicon Architecture Engineer, Intel Corporation "As a long-time researcher in programming languages and high-performance computing, I find the coverage of Automata and Computability in this book illuminating from a foundational perspective as well as timely from a practical perspective. In addition to classical topics such as automata theory and parsing, it allows a student to interactively study via Jupyter notebooks a wide range of topics including grammar disambiguation, Boolean satisfiability, Post Correspondence and Lambda Calculus --- all important topics for students who aspire to become proficient in computer science." -Vivek Sarkar, Professor, School of Computer Science & Stephen Fleming Chair for Telecommunications, College of Computing, Georgia Institute of Technology "I have taught formal languages and automata theory for decades, and I have seen many, perhaps most, students struggle with the material because it is so abstract. I've often thought that computer science students would learn it better by programming it. Indeed, that's how I really learned these topics -- by implementing constructions directly in practical compiler generation and formal verification tools to do my research. Prof. Gopalakrishnan's approach is to have students learn by doing, while still going into greater depth than some purely pencil-and-paper courses." -Prof. David L. Dill, Donald E. Knuth Professor, Emeritus, in the School of Engineering, Stanford University "It is probably a safe assumption to make these days that many, if not most, computer science undergraduates have had programming experience, but few of them know the language of mathematics. Professor Gopalakrishnan’s book builds on the student’s experience in programming and animates the theory of automata, formal languages, and computability with actual programs which the student can easily modify and play with. Doing is the best way of learning. This book should enable the typical computer science student to acquire a more visceral, and therefore in the long run more useful, understanding of the theory." -Dr. Ching-Tsun Chou, Silicon Architecture Engineer, Intel Corporation "As a long-time researcher in programming languages and high-performance computing, I find the coverage of Automata and Computability in this book illuminating from a foundational perspective as well as timely from a practical perspective. In addition to classical topics such as automata theory and parsing, it allows a student to interactively study via Jupyter notebooks a wide range of topics including grammar disambiguation, Boolean satisfiability, Post Correspondence and Lambda Calculus --- all important topics for students who aspire to become proficient in computer science." -Vivek Sarkar, Professor, School of Computer Science & Stephen Fleming Chair for Telecommunications, College of Computing, Georgia Institute of Technology Table of ContentsI Foundations 1 What Machines Think 2 Defining Languages: Patterns in Sets of Strings 3 Kleene Star: Basic Method of defining Repetitious Patterns II Machines 4 Basics of DFAs 5 Designing DFA 6 Operations on DFA 7 Nondeterministic Finite Automata 8 Regular Expressions and NFA 9 NFA to RE conversion 10 Derivative-based Regular Expression Matching 11 Context-Free Languages and Grammars 12 Pushdown Automata 13 Turing Machines III Concepts 14 Interplay Between Formal Languages 15 Post Correspondence, and Other Undecidability Proofs 16 NP-Completeness 17 Binary Decision Diagrams as Minimal DFA 18 Computability using Lambdas

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Book SynopsisGroundbreaking mathematician Gregory Chaitin gives us the first book to posit that we can prove how Darwin’s theory of evolution works on a mathematical level. For years it has been received wisdom among most scientists that, just as Darwin claimed, all of the Earth’s life-forms evolved by blind chance. But does Darwin’s theory function on a purely mathematical level? Has there been enough time for evolution to produce the remarkable biological diversity we see around us? It’s a question no one has yet answered—in fact, no one has attempted to answer it until now. In this illuminating and provocative book, Gregory Chaitin elucidates the mathematical scheme he’s developed that can explain life itself, and examines the works of mathematical pioneers John von Neumann and Alan Turing through the lens of biology. Fascinating and thought-provoking, Proving Darwin makes clear how biology may have found its greatest ally in mathematics

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Book SynopsisEmphasizing the search for patterns within and between biological sequences, trees, and graphs, Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R shows how combinatorial pattern matching algorithms can solve computational biology problems that arise in the analysis of genomic, transcriptomic, proteomic, metabolomic, and interactomic data. It implements the algorithms in Perl and R, two widely used scripting languages in computational biology. The book provides a well-rounded explanation of traditional issues as well as an up-to-date account of more recent developments, such as graph similarity and search. It is organized around the specific algorithmic problems that arise when dealing with structures that are commonly found in computational biology, including biological sequences, trees, and graphs. For each of these structures, the author makes a clear distinction between problems that arise in the analysis of one strTrade ReviewI like the hands-on approach this book offers, and the very pedagogical structure it follows … . The book also has tons of examples, thoughtfully chosen and beautifully laid out … the book is very well-written and accessible, undoubtedly written by an author who takes great care in preparing his manuscripts and teaching about an area he enjoys working on.—Anthony Labarre, SIGACT News, July 2012This text provides a solid foundation to the field. It will work as a practical handbook for pattern matching applications in computational biology. —Michael Goldberg, Computing Reviews, February 2010… the book makes a clear distinction between problems that emerge in the analysis of the structure and in the comparative analysis of two or more structures. … Well-known computational biology tools that allow searching nucleotide and protein databases for local sequence alignment are based on CPM algorithms only. The techniques presented in this book go beyond that. … detailed algorithm solutions in pseudocode, full Perl and R implementation, and pointers to software and implementation are presented. This … is what makes Valiente’s effort unique. …—Ernesto D’Avanzo, Computing Reviews, February 2010… It is a well-sorted collection of pattern matching algorithms that are used to work with problems in computational biology. … You can find all of the sources on the author’s website, which come in handy when you actually want to use them, since you do not have to retype them. And there is an introduction to Perl as well as to R, showing how to decode DNA/RNA-triplets to amino acids and giving some basic overview over standard functions. … I certainly recommend this as an introduction and reference to some algorithms of pattern matching in computational biology. You actually learn how algorithms over the most important data types are designed in a straightforward, logical way. …—Jannik Pewny, IACR Book Reviews, 2009…after a few minutes of random browsing, I was left with a feeling of total appreciation of the book, admiration for Prof. Gabriel Valiente, and a realization that this book will be part of my fundamental library for me and my group from the moment it is published. There are so many good things to say that I do not know where to start. The organization is straightforward with major sections that extend from simple sequences to trees to graphs. … This parallel structure makes it easy to apply lessons used on the simplest object (sequences) to objects of medium (trees) and significant (graphs) difficulty. …a wonderful way to learn leveraging … The Perl is beautifully clear and the examples have already taught me how to improve my own code.—Michael Levitt, Professor and Chair, Department of Structural Biology, Stanford University, California, USA…Balancing a careful mixture of formal methods, programming, and examples, Gabriel Valiente has managed to harmoniously bridge languages and contents into a self-contained source of lasting influence. It is not difficult to predict that this book will be studied indifferently by the specialist of biology and computer science, helping each to walk a few steps toward the other. It will entice new generations of scholars to engage in its beautiful subject.—From the Foreword, Alberto Apostolico, Professor, College of Computing, Georgia Tech, Atlanta, USAUnlocks the power for R for Perl programmers, and vice versa. Reveals R to be a powerful and accessible tool for bioinformatics. The title is a mouthful, but the use of both R and Perl for bioinformatics is revealing.—Steven Skiena, Professor, Department of Computer Science, Stony Brook University, New York, USAI like the hands-on approach this book offers, and the very pedagogical structure it follows … . The book also has tons of examples, thoughtfully chosen and beautifully laid out … the book is very well-written and accessible, undoubtedly written by an author who takes great care in preparing his manuscripts and teaching about an area he enjoys working on.—Anthony Labarre, SIGACT News, July 2012This text provides a solid foundation to the field. It will work as a practical handbook for pattern matching applications in computational biology. —Michael Goldberg, Computing Reviews, February 2010… the book makes a clear distinction between problems that emerge in the analysis of the structure and in the comparative analysis of two or more structures. … Well-known computational biology tools that allow searching nucleotide and protein databases for local sequence alignment are based on CPM algorithms only. The techniques presented in this book go beyond that. … detailed algorithm solutions in pseudocode, full Perl and R implementation, and pointers to software and implementation are presented. This … is what makes Valiente’s effort unique. …—Ernesto D’Avanzo, Computing Reviews, February 2010… It is a well-sorted collection of pattern matching algorithms that are used to work with problems in computational biology. … You can find all of the sources on the author’s website, which come in handy when you actually want to use them, since you do not have to retype them. And there is an introduction to Perl as well as to R, showing how to decode DNA/RNA-triplets to amino acids and giving some basic overview over standard functions. … I certainly recommend this as an introduction and reference to some algorithms of pattern matching in computational biology. You actually learn how algorithms over the most important data types are designed in a straightforward, logical way. …—Jannik Pewny, IACR Book Reviews, 2009…after a few minutes of random browsing, I was left with a feeling of total appreciation of the book, admiration for Prof. Gabriel Valiente, and a realization that this book will be part of my fundamental library for me and my group from the moment it is published. There are so many good things to say that I do not know where to start. The organization is straightforward with major sections that extend from simple sequences to trees to graphs. … This parallel structure makes it easy to apply lessons used on the simplest object (sequences) to objects of medium (trees) and significant (graphs) difficulty. …a wonderful way to learn leveraging … The Perl is beautifully clear and the examples have already taught me how to improve my own code.—Michael Levitt, Professor and Chair, Department of Structural Biology, Stanford University, California, USA…Balancing a careful mixture of formal methods, programming, and examples, Gabriel Valiente has managed to harmoniously bridge languages and contents into a self-contained source of lasting influence. It is not difficult to predict that this book will be studied indifferently by the specialist of biology and computer science, helping each to walk a few steps toward the other. It will entice new generations of scholars to engage in its beautiful subject.—From the Foreword, Alberto Apostolico, Professor, College of Computing, Georgia Tech, Atlanta, USAUnlocks the power for R for Perl programmers, and vice versa. Reveals R to be a powerful and accessible tool for bioinformatics. The title is a mouthful, but the use of both R and Perl for bioinformatics is revealing.—Steven Skiena, Professor, Department of Computer Science, Stony Brook University, New York, USATable of ContentsIntroduction. SEQUENCE PATTERN MATCHING: Sequences. Simple Pattern Matching in Sequences. General Pattern Matching in Sequences. TREE PATTERN MATCHING: Trees. Simple Pattern Matching in Trees. General Pattern Matching in Trees. GRAPH PATTERN MATCHING: Graphs. Simple Pattern Matching in Graphs. General Pattern Matching in Graphs. Appendices. References. Index.

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Book Synopsis1 Group Representations.- 2 Representations of the Symmetric Group.- 3 Combinatorial Algorithms.- 4 Symmetric Functions.- 5 Applications and Generalizations.Trade ReviewFrom the reviews of the second edition: "This work is an introduction to the representation theory of the symmetric group. Unlike other books on the subject this text deals with the symmetric group from three different points of view: general representation theory, combinatorial algorithms and symmetric functions. ... This book is a digestible text for a graduate student and is also useful for a researcher in the field of algebraic combinatorics for reference." (Attila Maróti, Acta Scientiarum Mathematicarum, Vol. 68, 2002) "A classic gets even better. ... The edition has new material including the Novelli-Pak-Stoyanovskii bijective proof of the hook formula, Stanley’s proof of the sum of squares formula using differential posets, Fomin’s bijective proof of the sum of squares formula, group acting on posets and their use in proving unimodality, and chromatic symmetric functions." (David M. Bressoud, Zentralblatt MATH, Vol. 964, 2001)Table of Contents* Group Representations * Representations of the Symmetric Group * Combinatorial Algorithms * Symmetric Functions * Applications and Generalizations

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Book SynopsisA Course in Topological Combinatorics is the first undergraduate textbook on the field of topological combinatorics, a subject that has become an active and innovative research area in mathematics over the last thirty years with growing applications in math, computer science, and other applied areas.Trade Review“This book is an excellent introduction into the subject. … The book contains a lot of figures and each chapter ends with a group of exercises which help the reader in understanding the hard constructions and proofs. The book may serve for a one- or two-semester undergraduate course depending on the preliminary knowledges of the students.” (János Kincses, Acta Scientiarum Mathematicarum, Vol. 81 (3-4), 2015)“The present book … presents a sequence of combinatorial themes which have shown an affinity for topological methods … . This book is filled with extremely attractive mathematics … and bringing topology into the play of combinatorics and graph theory is a wonderfully elegant manoeuvre. Here it is carried out coherently, and on a pretty grand scale, and we are thus afforded the opportunity to encounter (algebraic) topology in a very seductive uniform context. What a marvelous thing!” (Michael Berg, MAA Reviews, July, 2013)“In the book’s four main chapters, Longueville (Univ. of Applied Sciences, Germany) addresses fair-division problems; graph coloring; graph property evasiveness; and embeddings and mappings. … Basic results of algebraic topology already have powerful consequences for analysis, but the subject’s arcana can look like art for art’s sake. The author’s charting of a novel application domain for a core subject makes this book an essential acquisition. Summing Up: Essential. Upper-division undergraduates and above.” (D. V. Feldman, Choice, Vol. 50 (8), April, 2013)“Topological combinatorics is concerned with the applications of the many powerful techniques of algebraic topology to problems in combinatorics. … The present book aims to give a clear and vivid presentation of some of the most beautiful and accessible results from the area. The text, based upon some courses by the author at Freie Universität Berlin, is designed for an advanced undergraduate student.” (Hirokazu Nishimura, zbMATH, Vol. 1273, 2013)Table of ContentsPreface.- List of Symbols and Typical Notation.- 1 Fair-Division Problems.- 2 Graph-Coloring Problems.- 3 Evasiveness of Graph Properties.- 4 Embedding and Mapping Problems.- A Basic Concepts from Graph Theory.- B Crash Course in Topology.- C Partially Ordered Sets, Order Complexes, and Their Topology.- D Groups and Group Actions.- E Some Results and Applications from Smith Theory.- References.- Index.

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Book SynopsisThe highlights of the book are three main theorems in the combinatorial theory of convex polytopes, known as the Dehn-Sommerville Relations, the Upper Bound Theorem and the Lower Bound Theorem.Table of Contents1 Convex Sets.- A7;1. The Affine Structure of ?d.- A7;2. Convex Sets.- A7;3. The Relative Interior of a Convex Set.- A7;4. Supporting Hyperplanes and Halfspaces.- A7;5. The Facial Structure of a Closed Convex Set.- A7;6. Polarity.- 2 Convex Polytopes.- A7;7. Polytopes.- A7;8. Polyhedral Sets.- A7;9. Polarity of Polytopes and Polyhedral Sets.- A7;10. Equivalence and Duality of Polytopes.- A7;11. Vertex-Figures.- A7;12. Simple and Simplicial Polytopes.- A7;13. Cyclic Polytopes.- A7;14. Neighbourly Polytopes.- A7;15. The Graph of a Polytope.- 3 Combinatorial Theory of Convex Polytopes.- A7;16. Eulerߣs Relation.- A7;17. The Dehn-Sommerville Relations.- A7;18. The Upper Bound Theorem.- A7;19. The Lower Bound Theorem.- A7;20. McMullenߣs Conditions.- Appendix 1 Lattices.- Appendix 2 Graphs.- Appendix 3 Combinatorial Identities.- Bibliographical Comments.- List of Symbols.

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Book SynopsisTrade ReviewThe style and the beauty make this book an excellent reading. Keep it on your coffee table or/and bed table and open it often, Asymptopia is a fascinating place." - Péter Hajnal, ACTA Sci. Math.Table of Contents An infinity of primes Stirling's formula Big Oh, little Oh and all that Integration in Asymptopia From integrals to sums Asymptotics of binomial coefficients (n k ) Unicyclic graphs Ramsey numbers Large deviations Primes Asymptotic geometry Algorithms Potpourri Really Big Numbers! Bibliography Index

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Book SynopsisLinear algebra and matrix theory are fundamental tools for almost every area of mathematics, both pure and applied. This book combines coverage of core topics with an introduction to some areas in which linear algebra plays a key role, for example, block designs, directed graphs, error correcting codes, and linear dynamical systems.Trade ReviewLinear Algebra and Matrices: Topics for a Second Course by Helene Shapiro succeeds brilliantly at its slated purpose which is hinted at by its title. It provides some innovative new ideas of what to cover in the second linear algebra course that is offered at many universities...[this book] would be my personal choice for a textbook when I next teach the second course for linear algebra at my university. I highly recommend this book, not only for use as a textbook, but also as a source of new ideas for what should be in the syllabus of the second course." - Rajesh Pereira, IMAGETable of Contents Preliminaries Inner product spaces and orthogonality Eigenvalues, eigenvectors, diagonalization, and triangularization The Jordan and Weyr canonical forms Unitary similarity and normal matrices Hermitian matrices Vector and matrix norms Some matrix factorizations Field of values Simultaneous triangularization Circulant and block cycle matrices Matrices of zeros and ones Block designs Hadamard matrices Graphs Directed graphs Nonnegative matrices Error correcting codes Linear dynamical systems Bibliography Index

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Book SynopsisTrade ReviewAsymptotic group theory is a recently emerging branch of group theory, that can be described as the study of groups whose order is finite—but large! Tao’s book is certainly a valuable introduction to that exciting new subject." - Alain Valette, Jahresbericht der Deutschen Mathematiker-VereinigungTable of Contents Expansion in Cayley graphs Expander graphs: Basic theory Expansion in Cayley graphs, and Kazhdan's property (T) Quasirandom groups The Balog-Szemeredi-Gowers lemma, and the Bourgain-Gamburd expansion machine Product theorems, pivot arguments, and the Larsen-Pink non-concentration inequality Non-concentration in subgroups Sieving and expanders Related articles Cayley graphs the algebra of groups The Lang-Weil bound The spectral theorem and its converses for unbounded self-adjoint operators Notes on Lie algebras Notes on groups of Lie type Bibliography Index

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Book SynopsisAn introductory and up-to-date course on game theory for mathematicians, economists and other scientists with a basic mathematical background. This self-contained book provides a formal description of classic game-theoretic concepts alongside rigorous proofs and illustrates the theory through abundant examples, applications, and exercises.Table of Contents Introduction to decision theory Strategic games Extensive games Games with incomplete information Fundamentals of cooperative games Applications of cooperative games Bibliography Notations Index Index of solution concepts Subject Index

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Book SynopsisIntroduces symbolic dynamics from a perspective of topological dynamical systems. After introducing symbolic and topological dynamics, the core of the book consists of discussions of subshifts of positive entropy, of zero entropy, other non-shift minimal action on the Cantor set, and the ergodic properties of these systems.Table of Contents First examples and general properties of subshifts Topological dynamics Subshifts of positive entropy Subshifts of zero entropy Further minimal Cantor systems Methods from ergodic theory Automata and linguistic complexity Miscellaneous background topics Solutions to exercises Bibliography Index

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Book SynopsisPresents an introductory and up-to-date course on game theory addressed to mathematicians and economists, and to other scientists having a basic mathematical background. The book is self-contained, providing a formal description of the classic game-theoretic concepts together with rigorous proofs of the main results in the field.Table of Contents Introduction to decision theory Strategic games Extensive games Games with incomplete information Fundamentals of cooperative games Applications of cooperative games Bibliography Notations Index Index of solution concepts Subject index.

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Basic Mathematics teaches you all the maths you need for everyday situations. If you are terrified by maths, this is the book for you.Do you shy away from using numbers? Basic Mathematics can help. An easy-to-follow guide, it will ensure you gain the confidence you need to tackle maths and overcome your fears. It offers simple explanations of all the key areas, including decimals, percentages, measurements and graphs, and applies them to everyday situations, games and puzzles to help you understand mathematics quickly and enjoyably.Everything you need is here in this one book. Each chapter includes clear explanations, worked examples and test questions. At the end of the book there are challenges and games to give you new and interesting ways to practise your new skills.

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Table of Contents1. Basic definitions.- 2. The invariant bilinear form and the generalized Casimir operator.- 3. Integrable representations and the Weyl group of a Kac-Moody algebra.- 4. Some properties of generalized Cartan matrices.- 5. Real and imaginary roots.- 6. Affine Lie algebras: the normalized invariant bilinear form, the root system and the Weyl group.- 7. Affine Lie algebras: the realization (case k = 1).- 8. Affine Lie algebras: the realization (case k = 2 or 3). Application to the classification of finite order automorphisms.- 9. Highest weight modules over the Lie algebra g(A).- 10. Integrable highest weight modules: the character formula.- 11. Integrable highest weight modules: the weight system, the contravariant Hermitian form and the restriction problem.- 12. Integrable highest weight modules over affine Lie algebras. Application to ?-function identities.- 13. Affine Lie algebras, theta functions and modular forms.- 14. The principal realization of the basic representation. Application to the KdV-type hierarchies of non-linear partial differential equations.- Index of notations and definitions.- References.

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Book SynopsisSet Theoretical Aspects of Real Analysis is built around a number of questions in real analysis and classical measure theory, which are of a set theoretic flavor. Accessible to graduate students, and researchers the beginning of the book presents introductory topics on real analysis and Lebesgue measure theory. These topics highlight the boundary between fundamental concepts of measurability and nonmeasurability for point sets and functions. The remainder of the book deals with more specialized material on set theoretical real analysis. The book focuses on certain logical and set theoretical aspects of real analysis. It is expected that the first eleven chapters can be used in a course on Lebesque measure theory that highlights the fundamental concepts of measurability and non-measurability for point sets and functions. Provided in the book are problems of varying difficulty that range from simple observations to advanced results. Relatively difficult Table of ContentsZF theory and some point sets on the real line. Countable versions of AC and real analysis. Uncountable versions of AC and Lebesgue nonmeasurable sets. The Continuum Hypothesis and Lebesgue nonmeasurable sets. Measurability properties of sets and functions. Radon measures and nonmeasurable sets. Real-valued step functions with strange measurability properties. Relationships between certain classical constructions of Lebesgue nonmeasurable sets. Measurability properties of Vitali sets. A relationship between the measurability and continuity of real-valued functions. A relationship between absolutely nonmeasurable functions and Sierpinski-Zygmund functions. Sums of absolutely nonmeasurable injective functions. A large group of absolutely nonmeasurable additive functions. Additive properties of certain classes of pathological functions. Absolutely nonmeasurable homomorphisms of commutative groups. Measurable and nonmeasurable sets with homogeneous sections. A combinatorial problem on translation invariant extensions of the Lebesgue measure. Countable almost invariant partitions of G-spaces. Nonmeasurable unions of measure zero sections of plane sets. Measurability properties of well-orderings. Appendices. Bibliography. Subject Index.

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Book SynopsisGraph Theory and Its Applications, Third Edition is the latest edition of the international, bestselling textbook for undergraduate courses in graph theory, yet it is expansive enough to be used for graduate courses as well. The textbook takes a comprehensive, accessible approach to graph theory, integrating careful exposition of classical developments with emerging methods, models, and practical needs. The authorsâ unparalleled treatment is an ideal text for a two-semester course and a variety of one-semester classes, from an introductory one-semester course to courses slanted toward classical graph theory, operations research, data structures and algorithms, or algebra and topology.Features of the Third Edition Expanded coverage on several topics (e.g., applications of graph coloring and tree-decompositions) Provides better coverage of algorithms and algebraic and topological graph theory than any otherTable of ContentsIntroduction to Graph Models Graphs and Digraphs. Common Families of Graphs. Graph Modeling Applications. Walks and Distance. Paths, Cycles, and Trees. Vertex and Edge Attributes. Structure and Representation Graph Isomorphism. Automorphism and Symmetry. Subgraphs. Some Graph Operations. Tests for Non-Isomorphism. Matrix Representation. More Graph Operations. Trees Characterizations and Properties of Trees. Rooted Trees, Ordered Trees, and Binary Trees. Binary-Tree Traversals. Binary-Search Trees. Huffman Trees and Optimal Prefix Codes. Priority Trees. Counting Labeled Trees. Counting Binary Trees. Spanning Trees Tree Growing. Depth-First and Breadth-First Search. Minimum Spanning Trees and Shortest Paths. Applications of Depth-First Search. Cycles, Edge-Cuts, and Spanning Trees. Graphs and Vector Spaces. Matroids and the Greedy Algorithm. Connectivity Vertex and Edge-Connectivity. Constructing Reliable Networks. Max-Min Duality and Menger’s Theorems. Block Decompositions. Optimal Graph Traversals Eulerian Trails and Tours. DeBruijn Sequences and Postman Problems. Hamiltonian Paths and Cycles. Gray Codes and Traveling Salesman Problems. Planarity and Kuratowski’s Theorem Planar Drawings and Some Basic Surfaces. Subdivision and Homeomorphism. Extending Planar Drawings. Kuratowski’s Theorem. Algebraic Tests for Planairty. Planarity Algorithm. Crossing Numbers and Thickness. Graph Colorings Vertex-Colorings. Map-Colorings. Edge-Colorings. Factorization. Special Digraph Models Directed Paths and Mutual Reachability. Digraphs as Models for Relations. Tournaments. Project Scheduling. Finding the Strong Components of a Digraph. Network Flows and Applications Flows and Cuts in Networks. Solving the Maximum-Flow Problem. Flows and Connectivity. Matchings, Transversals, and Vertex Covers. Graph Colorings and Symmetry Automorphisms of Simple Graphs. Equivalence Classes of Colorings. Appendix

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Trade Review“This book is an outstanding book on counting integer points of polytopes … . The book contains lots of exercises with very helpful hints. Another essential feature of the book is a vast collection of open problems on different aspects of integer point counting and related areas. … The book is reader-friendly written, self-contained and contains numerous beautiful illustrations. The reader is always accompanied with deep research jokes by famous researchers and valuable historical notes.” (Oleg Karpenkov, zbMATH 1339.52002, 2016)Reviews of the first edition:“You owe it to yourself to pick up a copy of Computing the Continuous Discretely to read about a number of interesting problems in geometry, number theory, and combinatorics.”— MAA Reviews“The book is written as an accessible and engaging textbook, with many examples, historical notes, pithy quotes, commentary integrating the material, exercises, open problems and an extensive bibliography.”— Zentralblatt MATH“This beautiful book presents, at a level suitable for advanced undergraduates, a fairly complete introduction to the problem of counting lattice points inside a convex polyhedron.”— Mathematical Reviews“Many departments recognize the need for capstone courses in which graduating students can see the tools they have acquired come together in some satisfying way. Beck and Robins have written the perfect text for such a course.”— CHOICETable of ContentsPreface.- The Coin-Exchange Problem of Frobenius.- A Gallery of Discrete Volumes.- Counting Lattice Points in Polytopes: The Ehrhart Theory.- Reciprocity.- Face Numbers and the Dehn-Sommerville Relations in Ehrhartian Terms.- Magic Squares.- Finite Fourier Analysis.- Dedekind Sums.- The Decomposition of a Polytope into Its Cones.- Euler-MacLaurin Summation in Rd.- Solid Angles.- A Discrete Version of Green's Theorem Using Elliptic Functions.- Appendix A: Triangulations of Polytopes.- Appendix B: Hints for Selected Exercises.- References.- Index.- List of Symbols.-

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Trade Review“The present book gives a detailed treatment of the standard monomial theory (SMT) for the Grassmannians and their Schubert subvarieties along with several applications of SMT. It can be used as a reference book by experts and graduate students who study varieties with a reductive group action such as flag and toric varieties.” (Valentina Kiritchenko, zbMATH 1343.14001, 2016)“The book under review is more elementary; it is exclusively devoted to Grassmannians and their Schubert subvarieties. The book is divided into three parts. … This is a nicely written book, one that may appeal to students and researchers in related areas.” (Felipe Zaldivar, MAA Reviews, maa.org, December, 2015)Table of ContentsPreface.- 1. Introduction.- Part I. Algebraic Geometry—A Brief Recollection - 2. Preliminary Material.- 3. Cohomology Theory.- 4. Gröbner Bases.- Part II. Grassmannian and Schubert Varieties.- 5. The Grassmannian and Its Schubert Varieties.- 6. Further Geometric Properties of Schubert Varieties.- 7. Flat Degenerations.- Part III. Flag Varieties and Related Varieties.- 8. The Flag Variety: Geometric and Representation-Theoretic Aspects.- 9. Relationship to Classical Invariant Theory.- 10. Determinantal Varieties.- 11. Related Topics.- References.- List of Symbols.- Index.

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