Evolutionary Algorithms in Engineering Applications

Zbigniew Michalewicz

ISBN 10: 3540620214 / ISBN 13: 9783540620211

Published by Springer Berlin Heidelberg, 1997

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Evolutionary algorithms are general-purpose search procedures based on the mechanisms of natural selection and population genetics. They are appealing because they are simple, easy to interface, and easy to extend. This volume is concerned with applications of evolutionary algorithms and associated strategies in engineering. It will be useful for engineers, designers, developers, and researchers in any scientific discipline interested in the applications of evolutionary algorithms. The volume consists of five parts, each with four or five chapters. The topics are chosen to emphasize application areas in different fields of engineering. Each chapter can be used for self-study or as a reference by practitioners to help them apply evolutionary algorithms to problems in their engineering domains.

Seller Inventory # 9783540620211

Bibliographic Details

• Title: Evolutionary Algorithms in Engineering Applications
• Publisher: Springer Berlin Heidelberg
• Publication Date: 1997
• Language: English
• ISBN 10: 3540620214
• ISBN 13: 9783540620211
• Binding: Buch
• Condition: Neu

About this title

Synopsis

Evolutionary algorithms are general-purpose search procedures based on the mechanisms of natural selection and population genetics. They are appealing because they are simple, easy to interface, and easy to extend. This volume is concerned with applications of evolutionary algorithms and associated strategies in engineering. It will be useful for engineers, designers, developers, and researchers in any scientific discipline interested in the applications of evolutionary algorithms. The volume consists of five parts, each with four or five chapters. The topics are chosen to emphasize application areas in different fields of engineering. Each chapter can be used for self-study or as a reference by practitioners to help them apply evolutionary algorithms to problems in their engineering domains.