Modern heuristic techniques for combinatorial problems

著者

書誌事項

Modern heuristic techniques for combinatorial problems

edited by Colin R Reeves

（Advanced topics in computer science series）

McGraw-Hill Book Co., c1995

大学図書館所蔵 件 / 全1件

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

This introductory text describes types of heuristic procedures for solving large combinatorial problems. Some of the techniques covered include simulated annealing and tabu search, Lagrangian relaxation, genetic algorithms and artificial neural networks.

目次

  • Introduction: Combinatorial Problems. Local and Global Optima. Heuristics. Simulated Annealing: Basic Method. Enhancements and Modifications. Applications. Tabu Search: Framework. Broader Aspects of Intensification and Diversification. Tabu Search Applications. Connections. Genetic Algorithms: Basic Concepts
  • Simple Example. Extensions and Modifications. Applications. Artificial Neural Networks: Neural Networks. Combinatorial Optimisation Problems. Graph Bisection Problem. Graph Partition Problem. The Travelling Salesman Problem. Scheduling Problems. Deformable Templates. Inequality Constraints. Lagrangian Relaxation: Basic Methodology. Lagrangian Heuristics and Problem Reduction. Determination of Legrange Multipliers. Dual Ascent. Tree Search. Application. Evaluation Of Heuristic Performance: Analytical Methods. Empirical Testing. Statistical Inference.

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