Evolutionary algorithms for single and multicriteria design optimization

Bibliographic Information

Evolutionary algorithms for single and multicriteria design optimization

Andrzej Osyczka

(Studies in fuzziness and soft computing, v. 79)

Physica-Verlag, c2002

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Includes bibliographical references and index

Description and Table of Contents

Description

Many design optimization problems are of a very complex nature and quite hard to solve by conventional optimization techniques. Genetic and evolutionary algorithms have recently received considerable attention because of their potential of being a very effective design optimization technique. The book starts with an introduction to design optimization which is followed by a description of genetic and evolutionary algorithms. Then the advanced evolutionary algorithm techniques are provided. These techniques are used in the single and multicriteria optimization methods described in this book. Finally three real-life design optimization problems are formulated and solved by means of these methods. The book is designed as a self-study guide for researchers and students in all engineering departments, especially in mechanical, civil and industrial engineering. The book may also be useful as a comprehensive text for operations researchers, artifical intelligence researchers.

Table of Contents

Introduction to Design Optimization.- Genetic and Evolutionary Algorithms as a Design Optimization Tool.- Advanced Evolutionary Algorithm Techniques.- Evolutionary Algorithms for Single Criterion Optimization.- Evolutionary Algorithms for Multicriteria Optimization.- Some Other Evolutionary Algorithms Based Methods.- Design Optimization Examples and Their Solution by Evolutionary Algorithms.- Appendix: Evolutionary Optimization System.- Appendix: C Codes for Two Design Optimization.

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