Optimization Books
Springer Biofuel Production Performance and Emission
Book SynopsisPreface.- Introduction to Renewable Energy Resources and Sustainable Feedstocks for Biodiesel.- Studies on oil extraction, biodiesel production methods, and engine performance and emission characteristic.- Experimentation, Modelling, and Analysis of Biodiesel conversion and their engine performance and emission characteristics.- Artificial Intelligence Modelling of engine performance and emission characteristic.- Optimization of engine performance and emission characteristics.
£89.99
Springer Analysis Approximation Optimization Computation and Applications
Book SynopsisPart I Introduction.- Chapter 1 The Life Path and Scientific Career of Academician ProfessorGradimir V. Milovanovic.- Part II Contributed Chapters.- Chapter 2 Shift-Invariant Subspaces of Sobolev Spaces and Shift-Preserving Operators.- Chapter 3 Multicriteria Model with a Dominant Criterion in Satisfaction and Non-Satisfaction.- Chapter 4 Enhanced Averaged Quadrature Rules with Application to Error Estimation.- Chapter 5 A Curious Hypergeometric Identity and Perfectness of Meixner–Sorokin System of Weights.- Chapter 6 On Reverse Triangle Inequality and some its Applications.- Chapter 7 Classical Karamata Theory of Regular Variability and the Index Function Operator.- Chapter 8 A note on Laguerre Truncated Polynomials and QuadratureFormula.- Chapter 9 An Optimal Quadrature Formula with Derivative in the Hilbert Space.- Chapter 10 Dynamics of Operators on the Space of Radon Measures.- Chapter 11 Error Estimates of Gaussian-type Quadratures – A Survey.- Chapter 12 Partitions and Automorphisms of Finite Kurepa Trees.- Chapter 13 Karamata’s Theory, Asymptotic Relations and the Generalized Inverse.- Chapter 14 Optimal Solutions of System of ( ?? , ??)-Hilfer FDEs via BestProximity Point using MNC.- Chapter 15 Iterative Methods for the Inclusion of the Inverse Matrix.- Chapter 16 The Optimal Quadrature Formula for the Approximate Calculation of Fourier Coefficients in the Space f??2 (2,1) of Periodic Functions.- Chapter 17 On Almost Deferred Sequence Spaces Defined by Infinite Matrix.- Chapter 18 Certain Classes of Combinatorial Polynomials Involving (Inverse) Binomial Coefficients with their Applications.- Chapter 19 The Finite Difference Method for Solution of Parabolic Problem with Time-Dependent Coefficients.- Chapter 20 Quadrature Rules for Trigonometric Polynomials.- Chapter 21 A Boubaker Collocation Method to Solve the Single Degree of Freedom System.- Chapter 22 New Multiplicative Method of Multicriteria Analysis.
£124.92
Springer Geometry and NonConvex Optimization
Book SynopsisPreface.- Chapter 1 Hermite-Hadamard Like Inequalities Involving Generalized Bi-Convex Functions.- Chapter 2 Some properties of Barrelled and of Bornological locally convex spaces over an arbitrary complete valued field.- Chapter 3 Bounds for the Unweighted Jensen's Gap of Absolutely Continuous Functions.- Chapter 4 Test Instances for Multiobjective Mixed-Integer Nonlinear Optimization.- Chapter 5 A trace operator for weighted Sobolev spaces.- Chapter 6 Common fixed point results for Meir-Keeler type contraction mappings.- Chapter 7 Optimum Statistical Analysis on Sphere Surface.- Chapter 8 New Generalized Ostrowski Type Fractional Integral Inequalities.- Chapter 9 Genaralized Fractional Hilbert Type Integral Inequalities in Banach Spaces.- Chapter 10 Ternary derivation-homomorphism functional inequalities.- Chapter 11 C*-ternary biderivations and C*-ternary bihomomorphisms.- Chapter 12 A Survey of Erdos-Szekeres Products.- Chapter 13 Recent developments in general quasi variational inequality.- Chapter 14 General Variational Inequalities and Optimization.- Chapter 15 Characterizations and Set Theoretic Properties of Some Generalized Open and Fat Sets in Relator Spaces.- Chapter 16 Direct Continuity Properties of Relations in Relator Spaces.- Chapter 17 Variational Principles and Fixed Points in Symmetric Structures.- Chapter 18 Sequential Coercivity over Q-Ordered Q-Metric Spaces.- Chapter 19 A Hardy-Hilbert’s Integral Inequality with the Internal Variables Involving Two Derivative Functions.
£164.41
Springer Optimal Quadratic Programming and QCQP Algorithms with Case Studies
Book SynopsisPreface.- Part I Background.- Chapter 1 Linear Algebra.- Chapter 2 Optimization.- Part II Basic Algorithms.- Chapter 3 Gradient Methods.- Chapter 4 Conjugate Gradients as Direct Method.- Chapter 5 Gradient Projection.- Chapter 6 From Penalty to Exact Augmented Lagrangians.- Chapter 7 Active Sets with Finite Termination.- Part III Optimal Algorithms.- Chapter 8 Conjugate Gradients as Iterative Method.- Chapter 9 SMALE for Equality Constraints.- Chapter 10 MPRGP for Bound Constraints.- Chapter 11 MPGP and PBBF for Separable QCQP.- Chapter 12 Solvers for Separable and Equality QP/QCQP Problems.- Part IV Case Studies.- Chapter 13 Elliptic Variational Inequalities.- Chapter 14 Contact Problem with Friction.- Chapter 15 Model Predictive Control.- Chapter 16 Support Vector Machines.- Chapter 17 PERMON and ESPRESO Software.- References.
£116.99
Springer Turnpike Phenomenon for Markov Decision Processes
Book Synopsis1. Introduction.- 2. Uniqueness and stability of optimal policies.- 3. Existence of an overtaking optimal policy.- 4. A weak turnpike property.- 5. Convex Markov decision processes.- 6. Turnpike properties for MDPs with perturbations.- 7. Controllability properties.- 8. Optimal control problems with singleton-turnpikes.- 9. Conclusions.
£42.74
Walter de Gruyter Math Optimization for Artificial Intelligence
Book Synopsis
£129.67
De Gruyter Operational Perspective of Modeling System
Book Synopsis
£139.17
Springer Fachmedien Wiesbaden Numerische Verfahren der konvexen, nichtglatten
Book SynopsisKonvexe Optimierungsprobleme mit einer nichtglatten Zielfunktion treten in vielen Anwendungen auf, beispielsweise im Zusammenhang mit Penalty-Verfahren für differenzierbare Optimierungsprobleme, mit der Lagrange-Relaxation bei kombinatorischen Optimierungsproblemen oder bei der Strukturoptimierung von Stabwerken. Die wichtigsten numerischen Verfahren zur Lösung solcher Optimierungsprobleme sind Subgradienten- und Bundle-Verfahren. Das Buch gibt eine kompakte Einführung in die Grundlagen dieser Verfahren, die den Leser in die Lage versetzt, einfache Versionen der Verfahren selbst zu implementieren.Table of Contents1 Einführung.- 1.1 Konvexe Mengen und Funktionen.- 1.2 Konvexe Optimierungsaufgaben.- 1.3 Warum spezielle Verfahren?.- 2 Konvexe Mengen und Funktionen.- 2.1 Konvexe Mengen.- 2.2 Projektion auf konvexe Mengen.- 2.3 Trennungssätze.- 2.4 Konvexe Funktionen.- 2.5 Operationen mit konvexen Funktionen.- 2.6 Affine Minoranten.- 2.7 Lokale Lipschitz-Stetigkeit.- 2.8 Subdifferential und Richtungsableitung.- 2.9 Maximumfunktionen.- 3 Konvexe Optimierungsprobleme.- 3.1 Unrestringierte Probleme.- 3.2 Abstiegsrichtungen.- 3.3 Probleme mit allgemeinen konvexen Restriktionen.- 3.4 Lineare Nebenbedingungen.- 4 Das Subgradientenverfahren.- 4.1 Das Verfahren.- 4.2 Konvergenzbetrachtungen.- 4.3 Numerische Beispiele.- 5 Approximative Ableitungen.- 5.1 Approximation des Subdifferentials.- 5.2 Approximation der Richtungsableitung.- 5.3 Approximative Minima.- 5.4 Approximative Abstiegsrichtungen.- 6 Approximative Abstiegsverfahren.- 6.1 Grundlegende Verfahrenskonzepte.- 6.1.1 Verwendung eines Bundles.- 6.1.2 Approximative Suchrichtungen.- 6.1.3 Verfahren mit approximativer Suchrichtung.- 6.2 Das Schrittweitenverfahren.- 6.2.1 Iterative Berechnung der Schrittweite.- 6.2.2 Das Verfahren.- 6.2.3 Konvergenz des Schrittweitenverfahrens.- 6.3 Konstruktion des Bundles.- 6.4 Ein implementierbares Abstiegsverfahren.- 6.4.1 Das Verfahren.- 6.4.2 Konvergenz des Verfahrens.- 7 Bundle-Verfahren.- 7.1 Stopp-Kriterien.- 7.2 Allgemeiner Verfahrensablauf.- 7.3 Numerische Beispiele.- 8 Bundle-Trust-Region-Verfahren.- 8.1 Grundlage des Verfahrens.- 8.2 Das Trust-Region-Problem.- 8.3 Das Verfahrenskonzept.- 8.4 Implementierung des Verfahrens.- 8.4.1 Anpassung des Trust-Region-Parameters.- 8.4.2 Ein Abbruchkriterium.- 8.4.3 Kriterien für einen Abstiegsschritt.- 8.4.4 Kriterien für einen Nullschritt.- 8.4.5 Berechnung des Trust-Region-Parameters.- 8.4.6 Konstruktion des Bundles.- 8.5 Das Bundle-Trust-Region-Verfahren.- 8.6 Konvergenz des Verfahrens.- 8.7 Numerische Beispiele.- 8.8 Probleme mit linearen Restriktionen.- Übungsaufgaben.
£26.59
Springer Fachmedien Wiesbaden Numerik der Optimierung
Book Synopsis1 Optimierungsaufgaben und Optimalitätskriterien.- 1.1 Globale und lokale Optima, Konvexität.- 1.2 Optimalitätsbedingungen.- 1.3 Semiinfinite Probleme.- 1.4 Ganzzahlige Probleme.- 1.5 Optimierung über Graphen.- 2 Dualität.- 2.1 Duale Probleme.- 2.2 Gestörte Optimierungsprobleme.- 2.3 Anwendungen der Dualität.- 3 Minimierung ohne Restriktionen.- 3.1 Gradientenverfahren.- 3.2 Das Newton-Verfahren.- 3.3 Quasi-Newton-Verfahren.- 3.4 CG-Verfahren.- 3.5 Minimierung nichtglatter Funktionen.- 4 Linear restringierte Probleme.- 4.1 Polyedrische Mengen.- 4.2 Lineare Optimierung.- 4.3 Minimierung über Mannigfaltigkeiten.- 4.4 Probleme mit Ungleichungsrestriktionen.- 5 Strafmethoden.- 5.1 Das Grundprinzip von Strafmethoden.- 5.2 Konvergenzabschätzungen.- 5.3 Modifizierte Lagrange-Funktionen.- 5.4 Strafmethoden und elliptische Randwertprobleme.- 6 Approximationsverfahren.- 6.1 Verfahren der zulässigen Richtungen.- 6.2 Überlinear konvergente Verfahren.- 7 Komplexität.- 7.1 Definitionen, Polynomialität.- 7.2 Nichtdeterministisch polynomiale Algorithmen.- 7.3 Optimierungsprobleme und die Klasse NP-hart.- 7.4 Komplexität in der linearen Optimierung.- 8 Innere-Punkt-Methoden.- 8.1 Innerer-Pfad-Methode für lineare Probleme.- 8.2 Parameterfreies Potential.- 8.3 Der Algorithmus von Karmarkar.- 8.4 Komplementaritätsprobleme.- 8.5 Komplexität der linearen Optimierung.- 9 Aufgaben über Graphen.- 9.1 Definitionen.- 9.2 Graphen und lineare Optimierung.- 9.3 Aufdatierungen in Graphen.- 9.4 Probleme aus der Klasse NP-vollständig.- 10 Die Methode branch and bound.- 10.1 Relaxation, Separation, Strategien.- 10.2 Branch and bound für GLO.- 10.3 Das Rundreiseproblem.- 11 Dekomposition.- 11.1 Dekompositionsprinzipien.- 11.2 Dynamische Optimierung.- 11.3 Ausgewählte Anwendungen.- 12Strukturuntersuchungen.- 12.1 Ganzzahlige Polyeder.- 12.2 Gültige Ungleichungen.- 12.3 Matroide, Greedy-Algorithmus.Table of ContentsAufgabenstellung und Optimalitätskriterien - Dualität, Minimierung ohne Restriktionen - Optimierungsverfahren für linear restringierte Probleme - Penalty-Verfahren und modifizierte Lagrange-Methoden - Verfahren auf der Basis lokaler Approximationen - Komplexität - Innere-Punkt-Methoden - Graphentheoretische Modelle und Verfahren - Die Methode branch and bound - Dekompositionstechniken für strukturierte Optimierungsprobleme - Strukturuntersuchungen in ganzzahligen Optimierungsproblemen
£26.59
Springer Fachmedien Wiesbaden Grundlagen der Mathematischen Optimierung:
Book SynopsisDas Buch stellt wesentliche Ansätze, Ergebnisse und Methoden der linearen und ganzzahligen Optimierung dar. Ziel ist es, eine solide mathematische Grundlage des Gebietes und seiner wichtigsten algorithmischen Ansätze zu entwickeln. Methodisch zentral ist der geometrische Zugang.Table of ContentsEinleitung. - Einstiege: Ungleichungssysteme und diskrete Strukturen. - Einstiege: Algorithmen und Komplexität. - Konvexitätstheorie - Der Simplex-Algorithmus. - LP-Dualität.
£32.99
Springer Fachmedien Wiesbaden Mathematische Optimierung: Eine Einführung in die
Book SynopsisDas essential gibt Bachelor- und Masterstudierenden der Ingenieur- und Naturwissenschaften sowie der Wirtschaftswissenschaften eine kurze, anschauliche Einführung in die mathematische Optimierung. Anhand zahlreicher Beispiele werden die Grundbegriffe und Kernaussagen der kontinuierlichen Optimierung erläutert und angewendet. Es werden sowohl Optimierungsprobleme mit und ohne Nebenbedingungen als auch mehrkriterielle Probleme mit mehr als einer Zielfunktion behandelt.Table of ContentsBeispielprobleme: Ausgleichskurve, Standortplanung, Haltestellenproblem.- Optimalitätskriterien erster und zweiter Ordnung.- Karush-Kuhn-Tucker-Bedingungen, Pareto-optimale Lösungen und Pareto-Menge.- Methode der gewichteten Summe.
£11.77
Birkhauser Verlag AG Variational methods in some shape optimization
Book SynopsisThe study of shape optimization problems is a very wide field, both classical, as the isoperimetric problem and Newton problem of the best aerodynamical shape show, and modern, for all the recent results obtained in the last two, three decades. The fascinating feature is that the competing objects are shapes, i.e. domains of Rn, instead of functions, as usually occurs in problems of calculus of variations. This constraint often produces additional difficulties that lead to a lack of existence of a solution and the introduction of suitable relaxed formulations of the problem. However, in a few cases an optimal solution exists, due to the special form of the cost functional and to the geometrical restriction on the class of competing domains. This volume collects the lecture notes of two courses given in the academic year 2000/01 by the authors at the University of Pisa and at the Scuola Normale Superiore respectively. The courses were mainly addressed to Ph. D. students and required a background in the topics in functional analysis that are usually taught in undergraduate courses.
£18.19
Birkhauser Verlag AG Optimal Transportation, Geometry and Functional
Book SynopsisIn 2008, a school on the theory of optimal transportation and its applications took place in Pisa, with lectures by F. Barthe, W. Gangbo, F. Maggi and R. McCann. In this book, the notes of the first three lecturers are collected. They provide a deep insight on concentration inequalities, evolution PDEs of Hamiltonian type, geometric and functional inequalities.
£25.64
Birkhauser Verlag AG Geometric Partial Differential Equations
Book SynopsisThis book is the outcome of a conference held at the Centro De Giorgi of the Scuola Normale of Pisa in September 2012. The aim of the conference was to discuss recent results on nonlinear partial differential equations, and more specifically geometric evolutions and reaction-diffusion equations. Particular attention was paid to self-similar solutions, such as solitons and travelling waves, asymptotic behaviour, formation of singularities and qualitative properties of solutions. These problems arise in many models from Physics, Biology, Image Processing and Applied Mathematics in general, and have attracted a lot of attention in recent years.Table of ContentsN. Alikakos: On the structure of phase transition maps for three or more coexisting phases.- S. Amato, G. Bellettini, M. Paolini: The nonlinear multidomain model: a new formal asymptotic analysis.- A. Chambolle, M. Goldman, M. Novaga: Existence and qualitative properties of isoperimetric sets in periodic media.- A. Chambolle, M. Morini, M. Ponsiglione: Minimizing movements and level set approach to geometric flow of nonlocal perimeters.- S. Choi, I. Kim: Homogenization with oscillatory Neumann boundary data in general domain.- D. Christodoulou: The Analysis of Shock Formation in 3-Dimensional Fluids.- L. Dupaigne, A. Farina, B. Sirakov: Regularity of the extremal solutions for the Liouville system.- M.-H. Giga, Y. Giga, A. Nakayasu: On general existence results for one-dimensional singular diffusion equations with spatially inhomogeneous driving force.- Y. Giga, G. Pisante: On representation of boundary integrals involving the mean curvature for mean-convex domains.- A. Lemenant, Y. Sire: Elliptic problem in nonsmooth domain, Reifenberg-flat domains, Regularity.- A. Pisante: Maximally localized wannier functions: existence and exponential localization.- A. Stancu: Flows by powers of centro-affine curvature.
£24.69
Birkhauser Verlag AG Free Discontinuity Problems
Book SynopsisThis book presents a series of lectures on three of the best known examples of free discontinuity problems: the Mumford-Shah model for image segmentation, a variational model for the epitaxial growth of thin films, and the sharp interface limit of the Ohta-Kawasaki model for pattern formation in dyblock copolymers.Table of ContentsIntroduction.- Fine regularity results for Mumford-Shah minimizers: porosity, higher integrability and the Mumford-Shah conjecture.- Variational models for epitaxial growth.- Local and global minimality results for an isoperimetric problem with long-range interactions.
£21.84
Birkhauser Verlag AG Flows of Non-Smooth Vector Fields and Degenerate
Book SynopsisThe first part of the book is devoted to the transport equation for a given vector field, exploiting the lagrangian structure of solutions. It also treats the regularity of solutions of some degenerate elliptic equations, which appear in the eulerian counterpart of some transport models with congestion. The second part of the book deals with the lagrangian structure of solutions of the Vlasov-Poisson system, which describes the evolution of a system of particles under the self-induced gravitational/electrostatic field, and the existence of solutions of the semigeostrophic system, used in meteorology to describe the motion of large-scale oceanic/atmospheric flows.Table of ContentsAn overview on flows of vector fields and on optimal transport.- Maximal regular flows for non-smooth vector fields.- Main properties of maximal regular flows and analysis of blow-up.- Lagrangian structure of transport equations.- The continuity equation with an integrable damping term.- Regularity results for very degenerate elliptic equations.- An excess-decay result for a class of degenerate elliptic equations.- The Vlasov-Poisson system.- The semigeostrophic system.
£15.19
Springer Verlag, Singapore Compact and Fast Machine Learning Accelerator for
Book SynopsisThis book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator is presented from both algorithm level optimization and hardware architecture optimization. Coverage focuses on shallow and deep neural network with real applications on smart buildings. The authors also discuss hardware architecture design with coverage focusing on both CMOS based computing systems and the new emerging Resistive Random-Access Memory (RRAM) based systems. Detailed case studies such as indoor positioning, energy management and intrusion detection are also presented for smart buildings.Table of ContentsComputing on Edge Devices in Internet-of-things (IoT).- The Rise of Machine Learning in IoT system.- Least-squares-solver for Shadow Neural Network.- Tensor-solver for Deep Neural Network.- Distributed-solver for Networked Neural Network.- Conclusion.
£98.99
Springer Verlag, Singapore Optimization, Variational Analysis and
Book SynopsisThis book includes selected papers presented at the Indo-French Seminar on Optimization, Variational Analysis and Applications (IFSOVAA-2020), held at the Department of Mathematics, Institute of Science, Banaras Hindu University, Varanasi, India, from 2–4 February 2020. The book discusses current optimization problems and their solutions by using the powerful tool of variational analysis. Topics covered in this volume include set optimization, multiobjective optimization, mathematical programs with complementary, equilibrium, vanishing and switching constraints, copositive optimization, interval-valued optimization, sequential quadratic programming, bound-constrained optimization, variational inequalities, and more. Several applications in different branches of applied mathematics, engineering, economics, finance, and medical sciences have been included. Each chapter not only provides a detailed survey of the topic but also builds systematic theories and suitable algorithms to deduce the most recent findings in literature. This volume appeals to graduate students as well as researchers and practitioners in pure and applied mathematics and related fields that make use of variational analysis in solving optimization problems.Table of ContentsKhushboo and C. S. Lalitha, Linear and Pascoletti—Serafini Scalarizations in Unified Set Optimization.- N. K. Bisui, S. Mazumder and G. Panda, A Gradient Free Method for Multiobjective Optimization Problem.- J.-P. Dussault, T. Migot, M. Haddou, The New Butterfly Relaxation Method for Mathematical Programs with Complementarity Constraints.- S. K. Neogy and V. N. Mer, Copositive Optimization and its Applications in Graph Theory.- N Sharma, J. Bisht, and S. K. Mishra, Hermite-Hadamard type Inequalities for Functions whose Derivatives are Strongly-Convex via Fractional Integrals.- Q. H. Ansari, P. K. Sharma, Set Order Relations, Set Optimization and Ekeland’s Variational Principle.- A. K. Debnath and D. Ghosh, Characterizations and Generating Efficient Solutions to Interval Optimization Problems.- R. Sadhu, C. Nahak, S. P. Dash, Unconstrained Reformulation of Sequential Quadratic Programming and its Application in Convex Optimization.- P. Maréchal, A Note on Quadratic Penalties for Linear Ill-posed Problems: from Tikhonov Regularization to Mollification.- W. C. Simo Tao Lee.- A New Regularization Method for Linear Exponentially Ill-posed Problems.- V. Laha, H. N. Singh and S. K. Mishra, R. Kumar, On Minimax Programming with Vanishing Constraints.- B. B. Upadhyay and P. Mishra, On Minty Variational Principle for Nonsmooth Interval-Valued Multiobjective Programming Problems.- Y. Pandey, V. Singh, On Constraint Qualifications for Multiobjective Optimization Problems with Switching Constraints.- V. Kapoor and D. Nandan, Optimization of Physico-Chemical Parameters for the Production of Endoxylanase using Combined Response Surface Method and Genetic Algorithm.- A. Kaul, A. Gupta, S. Aggarwal, P. C. Jha, R. Ramanathan, Optimal Duration of Integrated Segment Specific and Mass Promotion Activities for Durable Technology Products: A Differential Evolution Approach.- M. Kumar, A Secure RGB Image Encryption Algorithm in Optimized Virtual Planet Domain.- J. D. Darbari, S. Sharma, M. C. Barrueta Pinto, Identification and Analysis of Key Sustainable Criteria for Third Party Reverse Logistics Provider Selection using the Best-Worst Method.- A. Gupta, N. Pachar, M. C. Barrueta Pinto, Efficiency Assessment through Peer Evaluation and Benchmarking: A Case Study of a Retail Chain using DEA.- R. K. Misra, D. Singh and A. Kumar, Spherical Search Algorithm: A Metaheuristic for Bound-Constrained Optimization.
£127.99
Springer Verlag, Singapore Smart and Intelligent Systems: Proceedings of SIS
Book SynopsisThis book is a collection of high-quality research papers presented at the International Conference on Smart and Intelligent Systems (SIS 2021), which will be held in Velagapudi Ramakrishna Siddhartha Engineering College (VRSEC), Andhra Pradesh, India, during February 25–26, 2021, in virtual mode. It highlights how recent informatics intelligent systems have successfully been used to develop innovative smart techniques and infrastructure in the field of modern engineering and technology. The book will also be of interest to those working in the field of computational intelligence, smart computer network and security analysis, control and automation system, cloud computing, fog computing and IoT, smart grid communication, smart cities, solar cell synthesis and their performance, green technology, and many more. The contents of this book prove useful to researchers and professionals.Table of ContentsOptimal Sizing and Siting of Distributed Generation for Losses Minimization in Distribution System using Fractional Lévy Flight Bat Algorithm.- Performance Analysis of a Standalone Inverter System under Variable Loading Conditions.- Performance Study of a Wind-Battery based Islanding System.- Fabric Defect Detection Using Computer Vision.- Energy Audit and Advancement of Solar Installation in SIT: A Case Study.- Random Fault Positioning Based Voltage Sag Assessment for a Large Power Transmission Network.- Feasibility Analysis of SEPIC Converter as a PV Balancer for Practical Photovoltaic System.- Market Clearing Mechanism by Optimal Scheduling of Electric Power Suppliers.- Anti Camcorder Piracy Display System.- Performance Evaluation of HAWT and VAWT based WECS with Advanced Hill Climb Search MPPT and Fuzzy Logic Controller for Low Wind Speed Regions.
£224.99
Springer Verlag, Singapore Emerging Frontiers in Operations and Supply Chain
Book SynopsisThis edited book addresses the challenges in managing the operations and supply chain of organizations in the era of internet of things and Industry 4.0. It presents cutting edge research on real world operations related problems, in-depth analyses, and relevant managerial implications. Wide variety of solution approaches such as quantitative, quantitative, and simulations are presented in the context of managing the operations and supply chains. Consisting of selected papers from the XXIII Annual International Conference of Society of Operations Management, this volume is part of a two volume series with the other book consisting of chapters on quantitative decision making. This edited book covers various quantitative models on operations and supply chain management such as inventory optimization, machine learning-operations research integrated model for healthcare systems, game-theoretic analysis of review strategies in truthful information sharing, design of contracts in supply chains, supply chain optimization, inventory routing, and shop floor scheduling. In addition to the quantitative models, several innovative heuristics are proposed for different problems. This book explores qualitative models on improving the performance of small and medium enterprises and petroleum industries and a simulation model for staff allocation in the information technology industry. Finally, this book provides review articles on vaccine supply chains and behavioral operations management.The book throws light on the emerging trends in the use of analytics, optimization, and simulation tools and empirical analysis to improve the performance of operations and supply chains of organizations. It will serve as an essential resource for practitioners, students, faculty members and scholars in operations management and related areas to gain knowledge and pursue high quality research on developments in areas such as managing the resource management and the solution methodology---innovative tools employed in addressing the real world problems and the different optimization techniques.Table of ContentsOptimization of Inventory and Transportation in Supply Chains.- Scheduling in Manufacturing and Service Systems.- Forecasting and Information Analysis in Supply Chains.- Soft Computing and Machine Learning Techniques and Applications in Operations and Supply Chain Management.- Logistics and Supply Chain Management in Healthcare Systems.- Applications of Game Theory and Revenue Management Principles in Supply Chain Management.
£132.99
Springer Verlag, Singapore Distributed Computing and Optimization
Book SynopsisThis book introduces research presented at the International Conference on Distributed Computing and Optimization Techniques (ICDCOT–2021), a two-day conference, where researchers, engineers, and academicians from all over the world came together to share their experiences and findings on all aspects of distributed computing and its applications in diverse areas. The book includes papers on distributed computing, intelligent system, optimization method, mathematical modeling, fuzzy logic, neural networks, grid computing, load balancing, communication. It will be a valuable resource for students, academics, and practitioners in the industry working on distributed computing.Table of Contents1. 1T-1D Single-Ended SRAM Cell Design for Low Power Applications using CMOS technology.- 2. A Local Descriptor and Histogram of Oriented Gradients for Makeup Invariant Face Recognition under Uncontrolled Environment.- 3. A Preventive Framework for Mine Representatives Utilizing Remote Sensor Networks with Optimized Routing.- 4. A Quantitative Study of Image Fusion using Hybrid Approach.- 5. A Review on Smart Road Traffic Management System using LoRa WAN.- 6. A Road Side Unit Based Proxy Signature Scheme for Fast Verification of Messages in Vehicular Ad-Hoc Network.- 7. A Secure Data Transmission using AODV and Hash Function for MANET.- 8. A Study on Different Types of Convolutions in Deep Learning in the Area of Lane Detection.- 9. A Study on the Impact of DC Appliances and Direct DC Power System in India.- 10. A Survey on Vehicle Detection and Classification for Electronic Toll Collection Applications
£116.99
Springer Verlag, Singapore Butterfly Optimization Algorithm: Theory and
Book SynopsisThis book presents theory and applications of recently introduced butterfly optimization algorithm (BOA). It also highlights hybridization process in the basic structure of BOA with in-depth analysis of complexity. This book also describes the constraint handling process. The newly introduced variant is implemented and validated on a set of linear and nonlinear real works problems of engineering and pulp and paper industry. The simulated results are compared with most of the basic algorithms. Comparative and nonparametric statistical result analysis illustrates the efficacy of the algorithm. Table of ContentsButterfly Optimization Algorithm.- Differential Butterfly Optimization Algorithm - A hybrid variant.- Application of DBOA in Structural Engineering Design Problems.- Application of DBOA in Pulp & Paper Process Optimization.- Conclusion and Future Directions.
£37.99
Springer Verlag, Singapore Performance Optimization of Fault Diagnosis
Book SynopsisThis book focuses on the performance optimization of fault diagnosis methods for power systems including both model-driven ones, such as the linear parameter varying algorithm, and data-driven ones, such as random matrix theory. Studies on fault diagnosis of power systems have long been the focus of electrical engineers and scientists. Pursuing a holistic approach to improve the accuracy and efficiency of existing methods, the underlying concepts toward several algorithms are introduced and then further applied in various situations for fault diagnosis of power systems in this book. The primary audience for the book would be the scholars and graduate students whose research topics including the control theory, applied mathematics, fault detection, and so on.Table of Contents- Chapter 1 Introduction.- Chapter 2 Fault Diagnosis of Variable Pitch for Wind Turbine Based on Multi-innovation Forgetting Gradient Identification Algorithm.- Chapter 3 Active Fault-tolerant Linear Parameter Varying Control for the Pitch Actuator of Wind Turbines.- Chapter 4 Fault Estimation and Fault-tolerant Control of Wind Turbines Using the SDW-LSI Algorithm.- Chapter 5 A New Fault Diagnosis Approach for the Pitch System of Wind Turbines.- Chapter 6 A dual-threshold state analysis and fault location method for power system based on random matrix theory.- Chapter 7 Analysis of grid operation state based on improved MESCM algorithm.- Chapter 8 Joint Weighted Domain Adaptation Network for Bearing Fault Diagnosis under Different Working Conditions.- Chapter 9 ANS-net: anti-noise Siamese network for bearing fault diagnosis with a few data.- Chapter 10 Fault Diagnosis of Rolling Bearing Based on Edge Calculation.
£80.99
Springer Verlag, Singapore Applications of Operational Research in Business
Book SynopsisEffective decision-making while trading off the constraints and conflicting multiple objectives under rapid technological developments, massive generation of data, and extreme volatility is of paramount importance to organizations to win over the time-based competition today. While agility is a crucial issue, the firms have been increasingly relying on evidence-based decision-making through intelligent decision support systems driven by computational intelligence and automation to achieve a competitive advantage. The decisions are no longer confined to a specific functional area. Instead, business organizations today find actionable insight for formulating future courses of action by integrating multiple objectives and perspectives. Therefore, multi-objective decision-making plays a critical role in businesses and industries. In this regard, the importance of Operations Research (OR) models and their applications enables the firms to derive optimum solutions subject to various constraints and/or objectives while considering multiple functional areas of the organizations together. Hence, researchers and practitioners have extensively applied OR models to solve various organizational issues related to manufacturing, service, supply chain and logistics management, human resource management, finance, and market analysis, among others. Further, OR models driven by AI have been enabled to provide intelligent decision-support frameworks for achieving sustainable development goals.The present issue provides a unique platform to showcase the contributions of the leading international experts on production systems and business from academia, industry, and government to discuss the issues in intelligent manufacturing, operations management, financial management, supply chain management, and Industry 4.0 in the Artificial Intelligence era. Some of the general (but not specific) scopes of this proceeding entail OR models such as Optimization and Control, Combinatorial Optimization, Queuing Theory, Resource Allocation Models, Linear and Nonlinear Programming Models, Multi-objective and multi-attribute Decision Models, Statistical Quality Control along with AI, Bayesian Data Analysis, Machine Learning and Econometrics and their applications vis-à-vis AI & Data-driven Production Management, Marketing and Retail Management, Financial Management, Human Resource Management, Operations Management, Smart Manufacturing & Industry 4.0, Supply Chain and Logistics Management, Digital Supply Network, Healthcare Administration, Inventory Management, consumer behavior, security analysis, and portfolio management and sustainability. The present issue shall be of interest to the faculty members, students, and scholars of various engineering and social science institutions and universities, along with the practitioners and policymakers of different industries and organizations.Table of ContentsChapter 1: Optimization of an inventory model with demand dependent on selling price and stock, nonlinear holding cost along with trade credit policy.- Chapter 2: Software Defect Prediction Through a Hybrid Approach Comprising of a Statistical Tool and a Machine Learning Model.- Chapter 3: Conservation of a prey species through optimal taxation: a model with Beddington-DeAngelis Functional Response.- Chapter 4: Investigate the reason for students' absenteeism in Engineering College in Fuzzy MCDM environment.- Chapter 5: Optimal inventory management policies for substitutable products considering non-instantaneous decay and cost of substitution.
£142.49
Springer Verlag, Singapore Sine Cosine Algorithm for Optimization
Book SynopsisThis open access book serves as a compact source of information on sine cosine algorithm (SCA) and a foundation for developing and advancing SCA and its applications. SCA is an easy, user-friendly, and strong candidate in the field of metaheuristics algorithms. Despite being a relatively new metaheuristic algorithm, it has achieved widespread acceptance among researchers due to its easy implementation and robust optimization capabilities. Its effectiveness and advantages have been demonstrated in various applications ranging from machine learning, engineering design, and wireless sensor network to environmental modeling. The book provides a comprehensive account of the SCA, including details of the underlying ideas, the modified versions, various applications, and a working MATLAB code for the basic SCA.Table of ContentsIntroduction.- Sine Cosine Algorithm.- Sine Cosine Algorithm for Multi-Objective Optimization.- Sine Cosine Algorithm for Discrete Optimization Problems.- Advancements in the Sine Cosine Algorithm.- Conclusion and Further Research Directions.
£23.74
Springer Verlag, Singapore Modeling Calcium Signaling
Book SynopsisThis book focuses on the fundamental processes involved in calcium signaling through fractional mathematical modeling.
£33.24
Springer Intelligent Optimization
Book SynopsisThis textbook comprehensively explores the foundational principles, algorithms, and applications of intelligent optimization, making it an ideal resource for both undergraduate and postgraduate artificial intelligence courses. It remains equally valuable for active researchers and individuals engaged in self-study. Serving as a significant reference, it delves into advanced topics within the evolutionary computation field, including multi-objective optimization, dynamic optimization, constrained optimization, robust optimization, expensive optimization, and other pivotal scientific studies related to optimization. Designed to be approachable and inclusive, this textbook equips readers with the essential mathematical background necessary for understanding intelligent optimization. It employs an accessible writing style, complemented by extensive pseudo-code and diagrams that vividly illustrate the mechanisms, principles, and algorithms of optimization. With a focus on practicality, th
£999.99
Springer Verlag, Singapore Artificial Intelligence Applications in Banking
Book SynopsisThis book discusses all aspects of money laundering, starting from traditional approach to financial crimes to artificial intelligence-enabled solutions. It also discusses the regulators approach to curb financial crimes and how syndication among financial institutions can create a robust ecosystem for monitoring and managing financial crimes. It opens with an introduction to financial crimes for a financial institution, the context of financial crimes, and its various participants. Various types of money laundering, terrorist financing, and dealing with watch list entities are also part of the discussion. Through its twelve chapters, the book provides an overview of ways in which financial institutions deal with financial crimes; various IT solutions for monitoring and managing financial crimes; data organization and governance in the financial crimes context; machine learning and artificial intelligence (AI) in financial crimes; customer-level transaction monitoring system; machine learning-driven alert optimization; AML investigation; bias and ethical pitfalls in machine learning; and enterprise-level AI-driven Financial Crime Investigation (FCI) unit. There is also an Appendix which contains a detailed review of various data sciences approaches that are popular among practitioners.The book discusses each topic through real-life experiences. It also leverages the experience of Chief Compliance Officers of some large organizations to showcase real challenges that heads of large organizations face while dealing with this sensitive topic. It thus delivers a hands-on guide for setting up, managing, and transforming into a best-in-class financial crimes management unit. It is thus an invaluable resource for researchers, students, corporates, and industry watchers alike.Table of ContentsChapter 1: Introduction to financial crimes and its participants.- Chapter 2: Anti financial crimes organization overview in a financial institution.- Chapter 3: Financial institutions approach to curbing and mitigating financial crimes.- Chapter 4: IT solutions for monitoring and managing financial crimes.- Chapter 5: Typical challenges faced by AML and compliance divisions.- Chapter 6: Applications of artificial intelligence and digitization in financial crimes.- Chapter 7: Data organization and governance in financial crimes.- Chapter 8: Machine learning approach to customer due diligence and watchlist monitoring.- Chapter 9: Applying machine learning for transaction monitoring to optimize false positives.- Chapter 10: application of network analysis to further improve detection of financial crimes.- Chapter 11: AML investigation and application of digitization and machine learning for saving investigation time.- Chapter 12: Futuristic enterprise level AI driven Financial Crime Investigation unit (FCU) for a financial institution.
£62.99
Springer International Publishing AG Pyomo — Optimization Modeling in Python
Book SynopsisThis book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. This second edition provides an expanded presentation of Pyomo’s modeling capabilities, providing a broader description of the software that will enable the user to develop and optimize models. Introductory chapters have been revised to extend tutorials; chapters that discuss advanced features now include the new functionalities added to Pyomo since the first edition including generalized disjunctive programming, mathematical programming with equilibrium constraints, and bilevel programming.Pyomo is an open source software package for formulating and solving large-scale optimization problems. The software extends the modeling approach supported by modern AML (Algebraic Modeling Language) tools. Pyomo is a flexible, extensible, and portable AML that is embedded in Python, a full-featured scripting language. Python is a powerful and dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions.Trade Review“This book provides a detailed guide to Pyomo for beginners and advanced users from undergraduate students to academic researchers to practitioners. … the book is a good software guide which I strongly recommend to anybody interested in looking for an alternative to commercial modeling languages in general or in learning or intensifying their Pyomo skills in particular.” (Christina Schenk, SIAM Review, Vol. 61 (1), March, 2019)Table of Contents1. Introduction.- Part I. An Introduction to Pyomo.- 2. Mathematical Modeling and Optimization.- 3. Pyomo Overview.- 4. Pyomo Models and Components.- 5. The Pyomo Command.- 6. Data Command Files.- Part II. Advanced Features and Extensions.- 7. Nonlinear Programming with Pyomo.- 8. Structured Modeling with Blocks.- 9. Generalized Disjunctive Programming.- 10. Stochastic Programming Extensions.- 11. Differential Algebraic Equations.- 12. Mathematical Programs with Equilibrium Constraints.- 13. Bilevel Programming.- 14. Scripting.- A. A Brief Python Tutorial.- Index.
£45.99
Oxford University Press Connections in Combinatorial Optimization
Book SynopsisGraph connectivities and submodular functions are two widely applied and fast developing fields of combinatorial optimization. This book not only includes the most recent results, but also highlights several surprising connections between diverse topics within combinatorial optimization. It offers a unified treatment of developments in the concepts and algorithmic methods of the area, starting from basic results on graphs, matroids and polyhedral combinatorics, through the advanced topics of connectivity issues of graphs and networks, to the abstract theory and applications of submodular optimization. Difficult theorems and algorithms are made accessible to graduate students in mathematics, computer science, operations research, informatics and communication. The book is not only a rich source of elegant material for an advanced course in combinatorial optimization, but it also serves as a reference for established researchers by providing efficient tools for applied areas like infocomTrade ReviewThe title of the book is wisely chosen: it deals, among other subjects, with graph connectivity, and it provides connections between graph theoretical results and underlying combinatorial structures...The book is readable for students, researchers, possibly also practitioners. * Mathematical Reviews *Table of ContentsPART I - BASIC COMBINATORIAL OPTIMIZATION; PART II - HIGHER-ORDER CONNECTIONS; PART III - SEMIMODULAR OPTIMIZATION
£130.62
Taylor & Francis Ltd Optimal Design for Nonlinear Response Models
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£58.89
Taylor & Francis Ltd Particle Swarm Optimisation Classical and Quantum Perspectives Chapman HallCRC Numerical Analysis and Scientific Computing Series
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£58.89
Taylor & Francis Ltd Applications of Advanced Optimization Techniques in Industrial Engineering
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£142.50
Taylor & Francis Ltd Linear and Nonlinear Waves in Microstructured Solids Homogenization and Asymptotic Approaches
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Taylor & Francis Ltd Linear and Nonlinear Waves in Microstructured Solids
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Taylor & Francis Ltd Algorithms for VariableSize Optimization
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Taylor & Francis Ltd Evolutionary Computation with Intelligent Systems
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Taylor & Francis Ltd Mathematical Analysis and Optimization for Economists
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Taylor & Francis Ltd Mathematical Analysis and Optimization for Economists
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Taylor & Francis Ltd Optimization of Multilayered Radar Absorbing Structures RAS using Nature Inspired Algorithm
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Taylor & Francis Ltd Optimization of Multilayered Radar Absorbing Structures RAS using Nature Inspired Algorithm
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Taylor & Francis Ltd Duality in Optimization and Variational Inequalities
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Taylor & Francis Ltd Computational Optimization
Book SynopsisThis textbook offers a guided tutorial that reviews the theoretical fundamentals while going through the practical examples used for constructing the computational frame, applied to various real-life models.Computational Optimization: Success in Practice will lead the readers through the entire process. They will start with the simple calculus examples of fitting data and basics of optimal control methods and end up constructing a multi-component framework for running PDE-constrained optimization. This framework will be assembled piece by piece; the readers may apply this process at the levels of complexity matching their current projects or research needs.By connecting examples with the theory and discussing the proper communication between them, the readers will learn the process of creating a big house. Moreover, they can use the framework exemplified in the book as the template for their research or course problems they will know how to change theTable of ContentsChapter 1. Introduction to Optimization. Chapter 2. Minimization Approaches for Functions of One Variable. Chapter 3. Generalized Optimization Framework. Chapter 4. Exploring Optimization Algorithms. Chapter 5. Line Search Algorithms. Chapter 6. Choosing Optimal Step Size. Chapter 7. Trust Region and Derivative-Free Methods. Chapter 8. Large-Scale and Constrained Optimization. Chapter 9. ODE-based Optimization. Chapter 10. Implementing Regularization Techniques. Chapter 11. Moving to PDE-based Optimization. Chapter 12. Sharing Multiple Software Environments.
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Cambridge University Press A First Course in Combinatorial Optimization 36 Cambridge Texts in Applied Mathematics Series Number 36
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Cambridge University Press Compliance Quantified
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Cambridge University Press Optimal Reliability Design
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Cambridge University Press Geometric Control Theory 52 Cambridge Studies in Advanced Mathematics Series Number 52
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Cambridge University Press Mathematical Programs with Equilibrium Constraints
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