Evolutionary Algorithms : The Role of Mutation and Recombination

William M. Spears

ISBN 10: 3540669507 / ISBN 13: 9783540669500

Published by Springer, Berlin, Springer Berlin Heidelberg, Springer, 2000

About this Item

Neuware - Despite decades of work in evolutionary algorithms, there remains a lot of uncertainty as to when it is beneficial or detrimental to use recombination or mutation. This book provides a characterization of the roles that recombination and mutation play in evolutionary algorithms. It integrates prior theoretical work and introduces new theoretical techniques for studying evolutionary algorithms. An aggregation algorithm for Markov chains is introduced which is useful for studying not only evolutionary algorithms specifically, but also complex systems in general. Practical consequences of the theory are explored and a novel method for comparing search and optimization algorithms is introduced. A focus on discrete rather than real-valued representations allows the book to bridge multiple communities, including evolutionary biologists and population geneticists.

Seller Inventory # 9783540669500

Bibliographic Details

• Title: Evolutionary Algorithms : The Role of Mutation and Recombination
• Publisher: Springer, Berlin, Springer Berlin Heidelberg, Springer
• Publication Date: 2000
• Language: English
• ISBN 10: 3540669507
• ISBN 13: 9783540669500
• Binding: Buch
• Condition: Neu
• Dimensions: 235W x 188H x 35D millimeters 235 millimeters width by 188 millimeters height by 35 millimeters depth
• Weight: 424 grams

About this title

Synopsis

Despite decades of work in evolutionary algorithms, there remains a lot of uncertainty as to when it is beneficial or detrimental to use recombination or mutation. This book provides a characterization of the roles that recombination and mutation play in evolutionary algorithms. It integrates prior theoretical work and introduces new theoretical techniques for studying evolutionary algorithms. An aggregation algorithm for Markov chains is introduced which is useful for studying not only evolutionary algorithms specifically, but also complex systems in general. Practical consequences of the theory are explored and a novel method for comparing search and optimization algorithms is introduced. A focus on discrete rather than real-valued representations allows the book to bridge multiple communities, including evolutionary biologists and population geneticists.