# Handbook of combinatorial optimization, 3. sējums

Dingzhu Du, Panos M. Pardalos
Springer Science & Business Media, 1998. gada 15. dec. - 2403 lappuses
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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### Saturs

 No Preemption 72 MultiStage Problems 86 Further Scheduling Models 110 Routing and Topology Embedding in Lightwave Networks 171 The Quadratic Assignment Problem 241 Single Machine Problems 249 QAP Polytopes 258 Exact Solution Methods 287
 Selected Algorithmic Techniques for Parallel Optimization 407 Multispace Search for Combinatorial Optimization 457 The Equitable Coloring of Graphs 543 Randomized Parallel Algorithms 567 Tabu Search 621 Introduction 709 Author Index 759 Subject Index 779

 Available Computer Codes for the QAP 302 Asymptotic Behavior 309 Algorithmic Aspects of Domination in Graphs 339
 Subject Index of Volumes 13 845 Autortiesības

### Atsauces uz šo grāmatu

 Scheduling: Theory, Algorithms, and SystemsMichael PinedoPriekšskatījums nav pieejams - 2008