Evolutionary Computation in Practice

Tina Yu

ISBN 10: 3540757708 / ISBN 13: 9783540757702

Published by Springer Berlin Heidelberg, 2008

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This book is loaded with examples in which computer scientists and engineers have used evolutionary computation-programs that mimic natural evolution-to solve real problems. They aren't abstract, mathematically intensive papers, but accounts of solving important problems, including tips from the authors on how to avoid common pitfalls, maximize the effectiveness and efficiency of the search process, and many other practical suggestions. Some of the authors have already won 'Humies'-Human Competitive Results Awards-for the work described in this book. I highly recommend it as a highly concentrated source of good problem-solving approaches that are applicable to many real-world problems.--Erik Goodman, Vice President, Red Cedar Technology, Inc.; Professor, Electrical & Computer Engineering, Michigan State University; and Founding Chair, ACM SIGEVO, the Special Interest Group on Genetic and Evolutionary Computation ofthe Association for Computing Machinery.

Seller Inventory # 9783540757702

Bibliographic Details

• Title: Evolutionary Computation in Practice
• Publisher: Springer Berlin Heidelberg
• Publication Date: 2008
• Language: English
• ISBN 10: 3540757708
• ISBN 13: 9783540757702
• Binding: Buch
• Condition: Neu

About this title

Synopsis

This book is loaded with examples in which computer scientists and engineers have used evolutionary computation - programs that mimic natural evolution - to solve many real-world problems. They aren’t abstract, mathematically intensive papers, but accounts of solving important problems, including tips from the authors on how to avoid common pitfalls, maximize the effectiveness and efficiency of the search process, and many other practical suggestions.

From the Back Cover

This book is loaded with examples in which computer scientists and engineers have used evolutionary computation―programs that mimic natural evolution―to solve real problems. They aren’t abstract, mathematically intensive papers, but accounts of solving important problems, including tips from the authors on how to avoid common pitfalls, maximize the effectiveness and efficiency of the search process, and many other practical suggestions. Some of the authors have already won "Humies"―Human Competitive Results Awards―for the work described in this book. I highly recommend it as a highly concentrated source of good problem-solving approaches that are applicable to many real-world problems.

--Erik Goodman, Vice President, Red Cedar Technology, Inc.; Professor, Electrical & Computer Engineering, Michigan State University; and Founding Chair, ACM SIGEVO, the Special Interest Group on Genetic and Evolutionary Computation of the Association for Computing Machinery