Handbook of combinatorial optimization

著者

• Du, Dingzhu
• Pardalos, P. M. (Panos M.)

書誌事項

Handbook of combinatorial optimization

edited by Ding-Zhu Du and Panos M. Pardalos

Kluwer Academic, c1998-1999

• : set
• v. 1
• v. 2
• v. 3
• supplement v. A

注記

Includes bibliographical references and index

内容説明・目次

巻冊次

v. 1 ISBN 9780792350187

内容説明

This is the first of a multi-volume set. The various volumes deal with several algorithmic approaches for discrete problems as well as with many combinatorial problems. Almost every aspect of the enormous field with emphasis on recent developments is covered. Each chapter is essentially expository in nature, but of scholarly treatment. This volume is addressed not only to researchers in discrete optimization, but to all scientists who use combinatorial optimization methods to model and solve problems.

目次

• Mixed-integer nonlinear optimization in process synthesis, C.S. Adjiman, et al
• approximate algorithms and heuristics for MAX-SAT, R. Battiti, M. Protasi
• connections between nonlinear programming and discrete optimization, F. Giannessi, F. Tardella
• interior point methods for combinatorial optimization, J.E. Mitchell et al
• knapsack problems, D. Pisinger, P. Toth
• fractional combinatorial optimization, T. Radzik
• reformulation-linearization techniques for discrete optimization problems, H.D. Sherali, W.P. Adams
• Grobner bases in integer programming, R.R. Thomas
• applications of set covering, set packing and set partitioning models - a survey, R.R. Vemuganti.

巻冊次

: set ISBN 9780792350194

内容説明

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).

目次

• Volume 1: Preface. Mixed-Integer Nonlinear Optimization in Process Synthesis
• C.S. Adjiman, et al. Approximate Algorithms and Heuristics for MAX-SAT
• R. Battiti, M. Protasi. Connections between Nonlinear Programming and Discrete Optimization
• F. Giannessi, F. Tardella. Interior Point Methods for Combinatorial Optimization
• J.E. Mitchell, et al. Knapsack Problems
• D. Pisinger, P. Toth. Fractional Combinatorial Optimization
• T. Radzik. Reformulation-Linearization Techniques for Discrete Optimization Problems
• H.D. Sherali, W.P. Adams. Groebner Bases in Integer Programming
• R.R. Thomas. Applications of Set Covering, Set Packing and Set Partitioning Models: A Survey
• R.R. Vemuganti. Volume 2: Preface. Efficient Algorithms for Geometric Shortest Path Query Problems
• D.Z. Chen. Computing Distances between Evolutionary Trees
• B. DasGupta, et al. Combinatorial Optimization and Coalition Games
• Xiaotie Deng. Steiner Minimal Trees: An Introduction, Parallel Computation, and Future Work
• F.C. Harris, Jr. Resource Allocation Problems
• N. Katoh, T. Ibaraki. Combinatorial Optimization in Clustering
• B. Mirkin, I. Muchnik. The Graph Coloring Problem: A Bibliographic Survey
• P.M. Pardalos, et al. Steiner Minimal Trees in E3: Theory, Algorithms, and Applications
• J. MacGregor Smith. Dynamical System Approaches to Combinatorial Optimization
• J. Starke, M. Schanz. On-Line Dominating Set Problems for Graphs
• Wen-Guey Tzeng. Optimization Problems in Optical Networks
• Peng-Jun Wan. Shortest Networks on Surfaces
• Jia Feng Weng. Minimum Weight Triangulation
• Yanfeng Xu. Optimization Applications in the Airline Industry
• Gang Yu, Jian Yang.Author Index. Subject Index. Volume 3: Preface. Semidefinite Relaxations, Multivariate Normal Distributions, and Order Statistics
• D. Bertsimas, Yingyu Ye. A Review of Machine Scheduling: Complexity, Algorithms and Approximability
• Bo Chen, et al. Routing and Topology Embedding in Lightwave Networks
• Feng Cao. The Quadratic Assignment Problem
• R.E. Burkard, et al. Algorithmic Aspects of Domination in Graphs
• G.J. Chang. Selected Algorithmic Techniques for Parallel Optimization
• R.C. Correa, et al. Multispace Search in Combinatorial Optimization
• Jun Gu. The Equitable Coloring of Graphs
• Ko-Wei Lih. Randomized Parallel Algorithms for Combinatorial Optimization
• S. Rajasekaran, J.D.P. Rolim. Tabu Search
• F. Glover, M. Laguna. Author Index. Subject Index. Author Index of Volumes 1 3. Subject Index of Volumes 1 3.

巻冊次

v. 3 ISBN 9780792352853

内容説明

This is the third 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.

巻冊次

v. 2 ISBN 9780792352938

内容説明

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.

巻冊次

supplement v. A ISBN 9780792359241

内容説明

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).

目次

• Preface. The Maximum Clique Problem
• I.M. Bomze, et al. Linear Assignment Problems and Extensions
• R.E. Burkard, E. Cela. Bin Packing Approximation Algorithms: Combinatorial Analysis
• E.G. Coffman, et al. Feedback Set Problems
• P. Festa, et al. Neural Networks Approaches for Combinatorial Optimization Problems
• T.B. Trafalis, S. Kasap. Frequency Assignment Problems
• R.A. Murphey, et al. Algorithms for the Satisfiability (SAT) Problem
• J. Gu, et al. The Steiner Ratio of Lp-planes
• J. Albrecht, D. Cieslik. A Cogitative Algorithm for Solving the Equal Circles Packing Problem
• W. Huang, et al. Author Index. Subject Index.

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詳細情報

• NII書誌ID(NCID): BA3902809X
• ISBN:
  • 0792350197
  • 0792350189
  • 0792352939
  • 0792352858
  • 0792359240
• 出版国コード: uk
• タイトル言語コード: eng
• 本文言語コード: eng
• 出版地: Boston ; London
• ページ数/冊数: 4 v.
• 大きさ: 25 cm
• 分類:
  • DC21 : 519.76
• 件名:
  • LCSH : Combinatorial optimization