{"product_id":"applied-integer-programming-9780470373064","title":"Applied Integer Programming","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eAn accessible treatment of the modeling and solution of integer programming problems, featuring modern applications and software\u003c\/b\u003e  \u003cp\u003eIn order to fully comprehend the algorithms associated with integer programming, it is important to understand not only \u003ci\u003ehow\u003c\/i\u003e algorithms work, but also \u003ci\u003ewhy\u003c\/i\u003e they work. \u003ci\u003eApplied Integer Programming\u003c\/i\u003e features a unique emphasis on this point, focusing on problem modeling and solution using commercial software. Taking an application-oriented approach, this book addresses the art and science of mathematical modeling related to the mixed integer programming (MIP) framework and discusses the algorithms and associated practices that enable those models to be solved most efficiently.\u003c\/p\u003e \u003cp\u003eThe book begins with coverage of successful applications, systematic modeling procedures, typical model types, transformation of non-MIP models, combinatorial optimization problem models, and automatic preprocessing to obtain a better formulation. Subsequ\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"Thoroughly classroom-tested, Applied integer programming is an excellent book for integer programming courses at the upper-undergraduate and graduate levels.\" (Mathematical Reviews, 2011)  \u003c\/p\u003e\u003cp\u003e \"The book is intended as a textbook for an application oriented course for senior undergraduate or postgraduate students, mainly with an engineering, business school, or applied mathematics background. Each chapter comes with several exercises, solutions of which are provided in an appendix. Many figures illustrate the flow of algorithms and other concepts.\" (\u003ci\u003eZentralblatt MATH\u003c\/i\u003e, 2010)\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePREFACE.  \u003cp\u003e\u003cb\u003ePART I MODELING.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Integer Programming.\u003c\/p\u003e \u003cp\u003e1.2 Standard Versus Nonstandard Forms.\u003c\/p\u003e \u003cp\u003e1.3 Combinatorial Optimization Problems.\u003c\/p\u003e \u003cp\u003e1.4 Successful Integer Programming Applications.\u003c\/p\u003e \u003cp\u003e1.5 Text Organization and Chapter Preview.\u003c\/p\u003e \u003cp\u003e1.6 Notes.\u003c\/p\u003e \u003cp\u003e1.7 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Modeling and Models.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Assumptions on Mixed Integer Programs.\u003c\/p\u003e \u003cp\u003e2.2 Modeling Process.\u003c\/p\u003e \u003cp\u003e2.3 Project Selection Problems.\u003c\/p\u003e \u003cp\u003e2.4 Production Planning Problems.\u003c\/p\u003e \u003cp\u003e2.5 Workforce\/Staff Scheduling Problems.\u003c\/p\u003e \u003cp\u003e2.6 Fixed-Charge Transportation and Distribution Problems.\u003c\/p\u003e \u003cp\u003e2.7 Multicommodity Network Flow Problem.\u003c\/p\u003e \u003cp\u003e2.8 Network Optimization Problems with Side Constraints.\u003c\/p\u003e \u003cp\u003e2.9 Supply Chain Planning Problems.\u003c\/p\u003e \u003cp\u003e2.10 Notes.\u003c\/p\u003e \u003cp\u003e2.11 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Transformation Using 0–1 Variables.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Transform Logical (Boolean) Expressions.\u003c\/p\u003e \u003cp\u003e3.2 Transform Nonbinary to 0–1 Variable.\u003c\/p\u003e \u003cp\u003e3.3 Transform Piecewise Linear Functions.\u003c\/p\u003e \u003cp\u003e3.4 Transform 0–1 Polynomial Functions.\u003c\/p\u003e \u003cp\u003e3.5 Transform Functions with Products of Binary and Continuous Variables: Bundle Pricing Problem.\u003c\/p\u003e \u003cp\u003e3.6 Transform Nonsimultaneous Constraints.\u003c\/p\u003e \u003cp\u003e3.7 Notes.\u003c\/p\u003e \u003cp\u003e3.8 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Better Formulation by Preprocessing.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Better Formulation.\u003c\/p\u003e \u003cp\u003e4.2 Automatic Problem Preprocessing.\u003c\/p\u003e \u003cp\u003e4.3 Tightening Bounds on Variables.\u003c\/p\u003e \u003cp\u003e4.4 Preprocessing Pure 0–1 Integer Programs.\u003c\/p\u003e \u003cp\u003e4.5 Decomposing a Problem into Independent Subproblems.\u003c\/p\u003e \u003cp\u003e4.6 Scaling the Coefficient Matrix.\u003c\/p\u003e \u003cp\u003e4.7 Notes.\u003c\/p\u003e \u003cp\u003e4.8 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Modeling Combinatorial Optimization Problems I.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction.\u003c\/p\u003e \u003cp\u003e5.2 Set Covering and Set Partitioning.\u003c\/p\u003e \u003cp\u003e5.3 Matching Problem.\u003c\/p\u003e \u003cp\u003e5.4 Cutting Stock Problem.\u003c\/p\u003e \u003cp\u003e5.5 Comparisons for Above Problems.\u003c\/p\u003e \u003cp\u003e5.6 Computational Complexity of COP.\u003c\/p\u003e \u003cp\u003e5.7 Notes.\u003c\/p\u003e \u003cp\u003e5.8 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Modeling Combinatorial Optimization Problems II.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Importance of Traveling Salesman Problem.\u003c\/p\u003e \u003cp\u003e6.2 Transformations to Traveling Salesman Problem.\u003c\/p\u003e \u003cp\u003e6.3 Applications of TSP.\u003c\/p\u003e \u003cp\u003e6.4 Formulating Asymmetric TSP.\u003c\/p\u003e \u003cp\u003e6.5 Formulating Symmetric TSP.\u003c\/p\u003e \u003cp\u003e6.6 Notes.\u003c\/p\u003e \u003cp\u003e6.7 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART II REVIEW OF LINEAR PROGRAMMING AND NETWORK FLOWS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Linear Programming—Fundamentals.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Review of Basic Linear Algebra.\u003c\/p\u003e \u003cp\u003e7.2 Uses of Elementary Row Operations.\u003c\/p\u003e \u003cp\u003e7.3 The Dual Linear Program.\u003c\/p\u003e \u003cp\u003e7.4 Relationships Between Primal and Dual Solutions.\u003c\/p\u003e \u003cp\u003e7.5 Notes.\u003c\/p\u003e \u003cp\u003e7.6 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Linear Programming: Geometric Concepts.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Geometric Solution.\u003c\/p\u003e \u003cp\u003e8.2 Convex Sets.\u003c\/p\u003e \u003cp\u003e8.3 Describing a Bounded Polyhedron.\u003c\/p\u003e \u003cp\u003e8.4 Describing Unbounded Polyhedron.\u003c\/p\u003e \u003cp\u003e8.5 Faces, Facets, and Dimension of a Polyhedron.\u003c\/p\u003e \u003cp\u003e8.6 Describing a Polyhedron by Facets.\u003c\/p\u003e \u003cp\u003e8.7 Correspondence Between Algebraic and Geometric Terms.\u003c\/p\u003e \u003cp\u003e8.8 Notes.\u003c\/p\u003e \u003cp\u003e8.9 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Linear Programming: Solution Methods.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Linear Programs in Canonical Form.\u003c\/p\u003e \u003cp\u003e9.2 Basic Feasible Solutions and Reduced Costs.\u003c\/p\u003e \u003cp\u003e9.3 The Simplex Method.\u003c\/p\u003e \u003cp\u003e9.4 Interpreting the Simplex Tableau.\u003c\/p\u003e \u003cp\u003e9.5 Geometric Interpretation of the Simplex Method.\u003c\/p\u003e \u003cp\u003e9.6 The Simplex Method for Upper Bounded Variables.\u003c\/p\u003e \u003cp\u003e9.7 The Dual Simplex Method.\u003c\/p\u003e \u003cp\u003e9.8 The Revised Simplex Method.\u003c\/p\u003e \u003cp\u003e9.9 Notes.\u003c\/p\u003e \u003cp\u003e9.10 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Network Optimization Problems and Solutions.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Network Fundamentals.\u003c\/p\u003e \u003cp\u003e10.2 A Class of Easy Network Problems.\u003c\/p\u003e \u003cp\u003e10.3 Totally Unimodular Matrices.\u003c\/p\u003e \u003cp\u003e10.4 The Network Simplex Method.\u003c\/p\u003e \u003cp\u003e10.5 Solution via LINGO.\u003c\/p\u003e \u003cp\u003e10.6 Notes.\u003c\/p\u003e \u003cp\u003e10.7 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART III SOLUTIONS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Classical Solution Approaches.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Branch-and-Bound Approach.\u003c\/p\u003e \u003cp\u003e11.2 Cutting Plane Approach.\u003c\/p\u003e \u003cp\u003e11.3 Group Theoretic Approach.\u003c\/p\u003e \u003cp\u003e11.4 Geometric Concepts.\u003c\/p\u003e \u003cp\u003e11.5 Notes.\u003c\/p\u003e \u003cp\u003e11.6 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Branch-and-Cut Approach.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction.\u003c\/p\u003e \u003cp\u003e12.2 Valid Inequalities.\u003c\/p\u003e \u003cp\u003e12.3 Cut Generating Techniques.\u003c\/p\u003e \u003cp\u003e12.4 Cuts Generated from Sets Involving Pure Integer Variables.\u003c\/p\u003e \u003cp\u003e12.5 Cuts Generated from Sets Involving Mixed Integer Variables.\u003c\/p\u003e \u003cp\u003e12.6 Cuts Generated from 0–1 Knapsack Sets.\u003c\/p\u003e \u003cp\u003e12.7 Cuts Generated from Sets Containing 0–1 Coefficients and 0–1 Variables.\u003c\/p\u003e \u003cp\u003e12.8 Cuts Generated from Sets with Special Structures.\u003c\/p\u003e \u003cp\u003e12.9 Notes.\u003c\/p\u003e \u003cp\u003e12.10 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Branch-and-Price Approach.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Concepts of Branch-and-Price.\u003c\/p\u003e \u003cp\u003e13.2 Dantzig–Wolfe Decomposition.\u003c\/p\u003e \u003cp\u003e13.3 Generalized Assignment Problem.\u003c\/p\u003e \u003cp\u003e13.4 GAP Example.\u003c\/p\u003e \u003cp\u003e13.5 Other Application Areas.\u003c\/p\u003e \u003cp\u003e13.6 Notes.\u003c\/p\u003e \u003cp\u003e13.7 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Solution via Heuristics, Relaxations, and Partitioning.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction.\u003c\/p\u003e \u003cp\u003e14.2 Overall Solution Strategy.\u003c\/p\u003e \u003cp\u003e14.3 Primal Solution via Heuristics.\u003c\/p\u003e \u003cp\u003e14.4 Dual Solution via Relaxation.\u003c\/p\u003e \u003cp\u003e14.5 Lagrangian Dual.\u003c\/p\u003e \u003cp\u003e14.6 Primal–Dual Solution via Benders’ Partitioning.\u003c\/p\u003e \u003cp\u003e14.7 Notes.\u003c\/p\u003e \u003cp\u003e14.8 Exercises.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Solutions with Commercial Software.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction.\u003c\/p\u003e \u003cp\u003e15.2 Typical IP Software Components.\u003c\/p\u003e \u003cp\u003e15.3 The AMPL Modeling Language.\u003c\/p\u003e \u003cp\u003e15.4 LINGO Modeling Language.\u003c\/p\u003e \u003cp\u003e15.5 MPL Modeling Language.\u003c\/p\u003e \u003cp\u003eREFERENCES.\u003c\/p\u003e \u003cp\u003eAPPENDIX: ANSWERS TO SELECTED EXERCISES.\u003c\/p\u003e \u003cp\u003eINDEX.\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49402317504855,"sku":"9780470373064","price":111.56,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780470373064.jpg?v=1730480051","url":"https:\/\/bookcurl.com\/products\/applied-integer-programming-9780470373064","provider":"Book Curl","version":"1.0","type":"link"}