Combinatorial Optimization:Algorithms and Complexity

Combinatorial Optimization:Algorithms and Complexity
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作者: ,
1998-01
版次: 1
ISBN: 9780486402581
定价: 187.50
装帧: 平装
开本: 其他
纸张: 胶版纸
页数: 528页
正文语种: 英语
  • Clearlywrittengraduate-leveltextconsiderstheSovietellipsoidalgorithmforlinearprogramming;efficientalgorithmsfornetworkflow,matching,spanningtrees,andmatroids;thetheoryofNP-completeproblems;approximationalgorithms,localsearchheuristicsforNP-completeproblems,more."Mathematicianswishingaself-containedintroductionneedlooknofurther." PREFACE TO THE DOVER EDITION PREFACE

    Chapter 1 OPTIMIZATION PROBLEMS

     1.1 Introduction

     1.2 Optimization Problems

     1.3 Neighborhoods

     1.4 Local and Global Optima

     1.5 Convex Sets and Functions

     1.6 Convex Programming Problems

     Problems

     Notes and References

     Appendix: Terminology and Notation

     A.1 Linear Algebra

     A.2 Graph Theory

     A.3 Pidgin Algol

    Chapter2 THE SIMPLEX ALGORITHM

     2.1  Forfns of the Linear Programming Problem

     2.2 Basic Feasible Solutions

     2.3 The Geometry of Linear Programs

      2.3.1  Linear and Affine Spaces

      2.3.2 Convex Polytopes

      2.3.3 Polytopes and LP

     2.4 Moving from bfs to bfs

     2.5 Organization of a Tableau

     2.6 Choosing a Profitable Column

     2.7 Degeneracy and Bland's Anticycling Algorithm

     2.8 Beginning the Simplex Algorithm

     2.9 Geometric Aspects of Pivoting

     Problems

     Notes and References

    Chapter 3 DUALITY

     3.1 The Dual of a Linear Program in General Form

     3.2 Complementary Slackness

     3.3 Farkas' Lemma

     3.4 The Shortest-Path Problem and Its Dual

     3.5 Dual Information in the Tableau

     3.6 The Dual Simplex Algorithm

     3.7 Interpretation of the Dual Simplex Algorithm

     Problems

     Notes and References

    Chapter 4 COMPUTATIONAL CONSIDERATIONS FOR THE SIMPLEX ALGORITHM

     4.1 The Revised Simplex Algorithm

     4.2 Computational Implications of the Revised Simple Algorithm

     4.3 The Max-Flow Problem and Its Solution by the Revised Method

     4.4 Dantzig-Wolfe Decomposition

     Problems

     Notes and References

    Chapter 5 THE PRIMAL-DUAL ALGORITHM

    Chapter 6 PRIMAL-DUAL ALGORITHMS FOR MAX-FLOW AND SHORTEST PATH:FORD-FULKERSON AND DIJKSTRA

    Chapter 7 PRIMAL-DUAL ALGORITHMS FOR MIN-COST FLOW

    Chapter 8 ALGORIT MS AND COMPLEXITY

    Chapter 9 EFFICIENT ALGORITHMS FOR THE  MAX-FLOW PROMBLEM

    Chapter 10 ALGORITHMS FOR MATCHING

    Chapter 11 WEIGHTED MATCHING

    Chapter 12 SPANNING TREES AND MATROIDS

    Chapter 13 INTEGER LINEAR PROGRAMMING

    Chapter 14 A CUTTING-PLANE ALGORITHM FOR INTEGER LINEAR PROGRAMS

    Chapter 15 NP-COM PLETE PROBLEMS

    Chapter 16 MORE ABOUT NP-COMPLETENESS

    Chapter 17 APPROXIMATION ALGORITHMS

    Chapter 18 BRANCH-AND-BOUND AND DYNAMIC PROGRAMMING

    Chapter 19 LOCAL SEARCH

    INDEX
  • 内容简介:
    Clearlywrittengraduate-leveltextconsiderstheSovietellipsoidalgorithmforlinearprogramming;efficientalgorithmsfornetworkflow,matching,spanningtrees,andmatroids;thetheoryofNP-completeproblems;approximationalgorithms,localsearchheuristicsforNP-completeproblems,more."Mathematicianswishingaself-containedintroductionneedlooknofurther."
  • 目录:
    PREFACE TO THE DOVER EDITION PREFACE

    Chapter 1 OPTIMIZATION PROBLEMS

     1.1 Introduction

     1.2 Optimization Problems

     1.3 Neighborhoods

     1.4 Local and Global Optima

     1.5 Convex Sets and Functions

     1.6 Convex Programming Problems

     Problems

     Notes and References

     Appendix: Terminology and Notation

     A.1 Linear Algebra

     A.2 Graph Theory

     A.3 Pidgin Algol

    Chapter2 THE SIMPLEX ALGORITHM

     2.1  Forfns of the Linear Programming Problem

     2.2 Basic Feasible Solutions

     2.3 The Geometry of Linear Programs

      2.3.1  Linear and Affine Spaces

      2.3.2 Convex Polytopes

      2.3.3 Polytopes and LP

     2.4 Moving from bfs to bfs

     2.5 Organization of a Tableau

     2.6 Choosing a Profitable Column

     2.7 Degeneracy and Bland's Anticycling Algorithm

     2.8 Beginning the Simplex Algorithm

     2.9 Geometric Aspects of Pivoting

     Problems

     Notes and References

    Chapter 3 DUALITY

     3.1 The Dual of a Linear Program in General Form

     3.2 Complementary Slackness

     3.3 Farkas' Lemma

     3.4 The Shortest-Path Problem and Its Dual

     3.5 Dual Information in the Tableau

     3.6 The Dual Simplex Algorithm

     3.7 Interpretation of the Dual Simplex Algorithm

     Problems

     Notes and References

    Chapter 4 COMPUTATIONAL CONSIDERATIONS FOR THE SIMPLEX ALGORITHM

     4.1 The Revised Simplex Algorithm

     4.2 Computational Implications of the Revised Simple Algorithm

     4.3 The Max-Flow Problem and Its Solution by the Revised Method

     4.4 Dantzig-Wolfe Decomposition

     Problems

     Notes and References

    Chapter 5 THE PRIMAL-DUAL ALGORITHM

    Chapter 6 PRIMAL-DUAL ALGORITHMS FOR MAX-FLOW AND SHORTEST PATH:FORD-FULKERSON AND DIJKSTRA

    Chapter 7 PRIMAL-DUAL ALGORITHMS FOR MIN-COST FLOW

    Chapter 8 ALGORIT MS AND COMPLEXITY

    Chapter 9 EFFICIENT ALGORITHMS FOR THE  MAX-FLOW PROMBLEM

    Chapter 10 ALGORITHMS FOR MATCHING

    Chapter 11 WEIGHTED MATCHING

    Chapter 12 SPANNING TREES AND MATROIDS

    Chapter 13 INTEGER LINEAR PROGRAMMING

    Chapter 14 A CUTTING-PLANE ALGORITHM FOR INTEGER LINEAR PROGRAMS

    Chapter 15 NP-COM PLETE PROBLEMS

    Chapter 16 MORE ABOUT NP-COMPLETENESS

    Chapter 17 APPROXIMATION ALGORITHMS

    Chapter 18 BRANCH-AND-BOUND AND DYNAMIC PROGRAMMING

    Chapter 19 LOCAL SEARCH

    INDEX
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