Modern heuristic techniques for combinatorial problems
Author(s)
Bibliographic Information
Modern heuristic techniques for combinatorial problems
（Advanced topics in computer science series）
McGraw-Hill Book Co., c1995
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Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
- 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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