Handbook of Combinatorial Optimization

The second edition of this 5-volume handbook is intended to be a basic yet comprehensive reference work in combinatorial optimization that will benefit newcomers and researchers for years to come.

Author: Panos M. Pardalos

Publisher: Springer

ISBN: 1441979964

Category: Mathematics

Page: 3409

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The second edition of this 5-volume handbook is intended to be a basic yet comprehensive reference work in combinatorial optimization that will benefit newcomers and researchers for years to come. This multi-volume work deals with several algorithmic approaches for discrete problems as well as with many combinatorial problems. The editors have brought together almost every aspect of this enormous field of combinatorial optimization, an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communications networks, and management science. An international team of 30-40 experts in the field form the editorial board. The Handbook of Combinatorial Optimization, second edition is addressed to all scientists who use combinatorial optimization methods to model and solve problems. Experts in the field as well as non-specialists will find the material stimulating and useful.
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Handbook of Combinatorial Optimization

Two important discover ies, the ellipsoid method (1979) and interior point approaches (1984) both provide polynomial time algorithms for linear programming. These algo rithms have had a profound effect in combinatorial optimization.

Author: Ding-Zhu Du

Publisher: Springer Science & Business Media

ISBN: 9781475730234

Category: Mathematics

Page: 648

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Combinatorial (or discrete) optimization is one of the most active fields in the interface of operations research, computer science, and applied math ematics. Combinatorial optimization problems arise in various applications, including communications network design, VLSI design, machine vision, air line crew scheduling, corporate planning, computer-aided design and man ufacturing, database query design, cellular telephone frequency assignment, constraint directed reasoning, and computational biology. Furthermore, combinatorial optimization problems occur in many diverse areas such as linear and integer programming, graph theory, artificial intelligence, and number theory. All these problems, when formulated mathematically as the minimization or maximization of a certain function defined on some domain, have a commonality of discreteness. Historically, combinatorial optimization starts with linear programming. Linear programming has an entire range of important applications including production planning and distribution, personnel assignment, finance, alloca tion of economic resources, circuit simulation, and control systems. Leonid Kantorovich and Tjalling Koopmans received the Nobel Prize (1975) for their work on the optimal allocation of resources. Two important discover ies, the ellipsoid method (1979) and interior point approaches (1984) both provide polynomial time algorithms for linear programming. These algo rithms have had a profound effect in combinatorial optimization. Many polynomial-time solvable combinatorial optimization problems are special cases of linear programming (e.g. matching and maximum flow). In addi tion, linear programming relaxations are often the basis for many approxi mation algorithms for solving NP-hard problems (e.g. dual heuristics).
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Handbook of Graph Theory Combinatorial Optimization and Algorithms

This handbook provides comprehensive coverage of basic concepts and recent developments in the field.

Author: Krishnaiyan Thulasiraman

Publisher: Chapman and Hall/CRC

ISBN: 1584885955

Category: Mathematics

Page: 992

View: 389

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This handbook provides comprehensive coverage of basic concepts and recent developments in the field. Focusing on design, proof of correctness, and complexity analysis, this volume presents a detailed discussion of algorithms that are useful in a variety of applications and offers an authoritative review of the current state of the art. Using figures to help illustrate the concepts, the book examines topics, such as incremental algorithms and online algorithms, that have yet to receive much attention but have great potential for future applications.
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Handbook of Combinatorics

Author: R.L. Graham

Publisher: Elsevier

ISBN: 9780444880024

Category: Mathematics

Page: 2198

View: 925

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One area of mathematics which has come to the fore in recent years is that of Combinatorics. The intense interest has been fuelled in large part by the increasing importance of computers, the needs of computer science and the demands from applications where discrete models play more and more important roles. In addition, many classical branches of mathematics have now come to recognize that combinatorial structures are essential components of many mathematical theories. Leading experts in all areas of combinatorics have contributed to this book. The Handbook of Combinatorics provides the working mathematician and computer scientist with an excellent overview of basic methods and paradigms. The book also covers important results and discusses current trends and issues across the whole spectrum of combinatorics. It is hoped that even specialists in the field will benefit from reading this handbook by learning a leading expert's coherent and individual view of the topic.
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Handbook of Combinatorial Optimization and Probability Theory

This handbook provides an introduction to the state of the art of the probability theory that is most directly applicable to combinatorial optimization, with discrete optimization problems for points in Euclidean space, such as the minimum ...

Author: Louisa A. May

Publisher:

ISBN: 1781540926

Category: Combinatorial optimization

Page: 392

View: 823

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This handbook provides an introduction to the state of the art of the probability theory that is most directly applicable to combinatorial optimization, with discrete optimization problems for points in Euclidean space, such as the minimum spanning tree, the traveling-salesman tour, and minimal-length matchings. There are several nongeometric optimization problems that receive full treatment, and these include the problems of the longest common subsequence and the longest increasing subsequence.
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Differential Evolution A Handbook for Global Permutation Based Combinatorial Optimization

This is the first book devoted entirely to Differential Evolution (DE) for global permutative-based combinatorial optimization.

Author: Godfrey C. Onwubolu

Publisher: Springer Science & Business Media

ISBN: 9783540921509

Category: Computers

Page: 211

View: 895

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This is the first book devoted entirely to Differential Evolution (DE) for global permutative-based combinatorial optimization. Since its original development, DE has mainly been applied to solving problems characterized by continuous parameters. This means that only a subset of real-world problems could be solved by the original, classical DE algorithm. This book presents in detail the various permutative-based combinatorial DE formulations by their initiators in an easy-to-follow manner, through extensive illustrations and computer code. It is a valuable resource for professionals and students interested in DE in order to have full potentials of DE at their disposal as a proven optimizer. All source programs in C and Mathematica programming languages are downloadable from the website of Springer.
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Handbook of Metaheuristics

The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics.

Author: Michel Gendreau

Publisher: Springer

ISBN: 9783319910864

Category: Business & Economics

Page: 604

View: 640

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The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book’s chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular.Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.
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Handbook of combinatorial optimization

HANDBOOK OF COMBINATORIAL OPTIMIZATION ( VOL . 2 ) D.-Z. Du and P.M. Pardalos ( Eds . ) pp . 159-260 © 1998 Kluwer Academic Publishers Resource Allocation ...

Author: Dingzhu Du

Publisher: Springer Science & Business Media

ISBN: 0792352939

Category: Science

Page: 2403

View: 616

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This is the second of a multi-volume set. The various volumes deal with several algorithmic approaches for discrete problems as well as with many combinatorial problems. The emphasis is on late-1990s developments. Each chapter is essentially expository in nature, but scholarly in its treatment.
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Handbook of Graph Theory Combinatorial Optimization and Algorithms

Author: Krishnaiyan "kt" Thulasiraman

Publisher: CRC Press

ISBN: 0367575167

Category:

Page: 1244

View: 704

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The fusion between graph theory and combinatorial optimization has led to theoretically profound and practically useful algorithms, yet there is no book that currently covers both areas together. Handbook of Graph Theory, Combinatorial Optimization, and Algorithms is the first to present a unified, comprehensive treatment of both graph theory and combinatorial optimization. Divided into 11 cohesive sections, the handbook's 44 chapters focus on graph theory, combinatorial optimization, and algorithmic issues. The book provides readers with the algorithmic and theoretical foundations to: Understand phenomena as shaped by their graph structures Develop needed algorithmic and optimization tools for the study of graph structures Design and plan graph structures that lead to certain desirable behavior With contributions from more than 40 worldwide experts, this handbook equips readers with the necessary techniques and tools to solve problems in a variety of applications. Readers gain exposure to the theoretical and algorithmic foundations of a wide range of topics in graph theory and combinatorial optimization, enabling them to identify (and hence solve) problems encountered in diverse disciplines, such as electrical, communication, computer, social, transportation, biological, and other networks.
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Handbook of Optimization in Telecommunications

This comprehensive handbook brings together experts who use optimization to solve problems that arise in telecommunications. It is the first book to cover in detail the field of optimization in telecommunications.

Author: Mauricio G.C. Resende

Publisher: Springer Science & Business Media

ISBN: 0387301658

Category: Mathematics

Page: 1134

View: 731

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This comprehensive handbook brings together experts who use optimization to solve problems that arise in telecommunications. It is the first book to cover in detail the field of optimization in telecommunications. Recent optimization developments that are frequently applied to telecommunications are covered. The spectrum of topics covered includes planning and design of telecommunication networks, routing, network protection, grooming, restoration, wireless communications, network location and assignment problems, Internet protocol, World Wide Web, and stochastic issues in telecommunications. The book’s objective is to provide a reference tool for the increasing number of scientists and engineers in telecommunications who depend upon optimization.
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Combinatorial Optimization Some Problems and Trends

A companion preprint, written by Martin Grötschel and myself as a chapter of the Handbook of Combinatorics, describes the state of the art, concentrating on the well-established methods and models like polyhedral combinatorics, and should ...

Author: DIMACS (GROUP)

Publisher:

ISBN: OCLC:33450597

Category: Combinatorial optimization

Page: 42

View: 499

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Abstract: "In this working paper I discuss some issues, with the aim of suggesting research topics for the DIMACS special year "Combinatorial Optimization". I plan to focus on the unorthodox, hoping that at least one of the areas I describe below will gain new momentum as a result of this special year. A companion preprint, written by Martin Grötschel and myself as a chapter of the Handbook of Combinatorics, describes the state of the art, concentrating on the well-established methods and models like polyhedral combinatorics, and should be available soon."
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Design and Analysis of Approximation Algorithms

This book is intended to be used as a textbook for graduate students studying theoretical computer science. It can also be used as a reference book for researchers in the area of design and analysis of approximation algorithms.

Author: Ding-Zhu Du

Publisher: Springer

ISBN: 1461417007

Category: Mathematics

Page: 440

View: 459

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This book is intended to be used as a textbook for graduate students studying theoretical computer science. It can also be used as a reference book for researchers in the area of design and analysis of approximation algorithms. Design and Analysis of Approximation Algorithms is a graduate course in theoretical computer science taught widely in the universities, both in the United States and abroad. There are, however, very few textbooks available for this course. Among those available in the market, most books follow a problem-oriented format; that is, they collected many important combinatorial optimization problems and their approximation algorithms, and organized them based on the types, or applications, of problems, such as geometric-type problems, algebraic-type problems, etc. Such arrangement of materials is perhaps convenient for a researcher to look for the problems and algorithms related to his/her work, but is difficult for a student to capture the ideas underlying the various algorithms. In the new book proposed here, we follow a more structured, technique-oriented presentation. We organize approximation algorithms into different chapters, based on the design techniques for the algorithms, so that the reader can study approximation algorithms of the same nature together. It helps the reader to better understand the design and analysis techniques for approximation algorithms, and also helps the teacher to present the ideas and techniques of approximation algorithms in a more unified way.
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Handbook of Memetic Algorithms

Although this book contains chapters written by multiple authors, a great attention has been given by the editors to make it a compact and smooth work which covers all the main areas of computational intelligence optimization.

Author: Ferrante Neri

Publisher: Springer

ISBN: 9783642232473

Category: Mathematics

Page: 370

View: 467

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Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various operators in order to address optimization problems. The combination and interaction amongst operators evolves and promotes the diffusion of the most successful units and generates an algorithmic behavior which can handle complex objective functions and hard fitness landscapes. “Handbook of Memetic Algorithms” organizes, in a structured way, all the the most important results in the field of MAs since their earliest definition until now. A broad review including various algorithmic solutions as well as successful applications is included in this book. Each class of optimization problems, such as constrained optimization, multi-objective optimization, continuous vs combinatorial problems, uncertainties, are analysed separately and, for each problem, memetic recipes for tackling the difficulties are given with some successful examples. Although this book contains chapters written by multiple authors, a great attention has been given by the editors to make it a compact and smooth work which covers all the main areas of computational intelligence optimization. It is not only a necessary read for researchers working in the research area, but also a useful handbook for practitioners and engineers who need to address real-world optimization problems. In addition, the book structure makes it an interesting work also for graduate students and researchers is related fields of mathematics and computer science.
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Handbook of Test Problems in Local and Global Optimization

This collection of challenging and well-designed test problems arising in literature studies also contains a wide spectrum of applications, including pooling/blending operations, heat exchanger network synthesis, homogeneous azeotropic ...

Author: Christodoulos A. Floudas

Publisher: Springer Science & Business Media

ISBN: 9781475730401

Category: Technology & Engineering

Page: 442

View: 309

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This collection of challenging and well-designed test problems arising in literature studies also contains a wide spectrum of applications, including pooling/blending operations, heat exchanger network synthesis, homogeneous azeotropic separation, and dynamic optimization and optimal control problems.
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Handbook of Approximation Algorithms and Metaheuristics

Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics.

Author: Teofilo F. Gonzalez

Publisher: CRC Press

ISBN: 9781351235419

Category: Computers

Page: 780

View: 915

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Handbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reoptimization, sensitivity analysis, and stability. Traditional applications covered include: bin packing, multi-dimensional packing, Steiner trees, traveling salesperson, scheduling, and related problems. Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering, networks (sensor and wireless), communication, bioinformatics search, streams, virtual communities, and more. About the Editor Teofilo F. Gonzalez is a professor emeritus of computer science at the University of California, Santa Barbara. He completed his Ph.D. in 1975 from the University of Minnesota. He taught at the University of Oklahoma, the Pennsylvania State University, and the University of Texas at Dallas, before joining the UCSB computer science faculty in 1984. He spent sabbatical leaves at the Monterrey Institute of Technology and Higher Education and Utrecht University. He is known for his highly cited pioneering research in the hardness of approximation; for his sublinear and best possible approximation algorithm for k-tMM clustering; for introducing the open-shop scheduling problem as well as algorithms for its solution that have found applications in numerous research areas; as well as for his research on problems in the areas of job scheduling, graph algorithms, computational geometry, message communication, wire routing, etc.
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