Evolutionary Computation
1st Edition
Published on 22. June 2000
424 pages
978-1-040-21342-1 (ISBN)
Description
Rapid advances in evolutionary computation have opened up a world of applications-a world rapidly growing and evolving. Decision making, neural networks, pattern recognition, complex optimization/search tasks, scheduling, control, automated programming, and cellular automata applications all rely on evolutionary computation.
Evolutionary Com
Evolutionary Com
Reviews / Votes
"...offers a presentation of the main ideas, models, and algorithms of evolutionary computation. Anyone who is inspired by the work of L. Davis or D.E. Goldberg to use evolutionary computation as a tool in hos/her daily work will find a complete overview of techniques and strategies...Anyone interested in optimization or search problems can find useful ideas, methods, and algorithms."- Journal of Chemometrics, 2002
More details
Series
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
ISBN-13
978-1-040-21342-1 (9781040213421)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
D. Dumitrescu | Beatrice Lazzerini | Lakhmi C. Jain
Evolutionary Computing and Applications
Book
06/2000
1st Edition
CRC Press
€328.07
Article not available at the moment
Persons
Beatrice Lazzerini, D. Dumitrescu, Lakhmi C. Jain. A. Dumitrescu
Content
Principles of Evolutionary Computation
Genetic Algorithms
Basic Selection Schemes in Evolutionary Algorithms
Selection Based on Scaling and Ranking Mechanisms
Further Selection Strategies
Recombination Operators within Binary Encoding
Mutation and other Search Operators
Schema Theorem, Building Blocks and Related Topics
Real-valued Encoding
Hybridization, Parameter Setting and Adaptation
Adaptive Representations: Messy Genetic Algorithms, Delta Coding and Diploidic Representation
Evolution Strategies and Evolutionary Programming
Population Models and Parallel Implementations
Genetic Programming
Learning Classifier Systems
Applications of Evolutionary Computation
Genetic Algorithms
Basic Selection Schemes in Evolutionary Algorithms
Selection Based on Scaling and Ranking Mechanisms
Further Selection Strategies
Recombination Operators within Binary Encoding
Mutation and other Search Operators
Schema Theorem, Building Blocks and Related Topics
Real-valued Encoding
Hybridization, Parameter Setting and Adaptation
Adaptive Representations: Messy Genetic Algorithms, Delta Coding and Diploidic Representation
Evolution Strategies and Evolutionary Programming
Population Models and Parallel Implementations
Genetic Programming
Learning Classifier Systems
Applications of Evolutionary Computation
