Evolutionary Computation 2: Advanced Algorithms and Operators

by Thomas Baeck (Editor)

Overview

Evolutionary Computation 2: Advanced Algorithms and Operators expands upon the basic ideas underlying evolutionary algorithms. The focus is on fitness evaluation, constraint-handling techniques, population structures, advanced techniques in evolutionary computation, and the implementation of evolutionary algorithms. It is intended to be used by individual researchers and students in the expanding field of evolutionary computation.

Product Details

ISBN-13:	9781138413078
Publisher:	Taylor & Francis
Publication date:	07/27/2017
Pages:	304
Product dimensions:	6.12(w) x 9.19(h) x (d)

Table of Contents

FITNESS EVALUATION Introduction to fitness evaluation Encoding and decoding functions Competitive fitness evaluation Complexity-based fitness evaluation Multiobjective optimization CONSTRAINT-HANDLING TECHNIQUES Introduction to constraint-handling techniques Penalty functions Decoders Repair algorithms Constraint-preserving operators Other constraint-handling methods Constraint-satisfaction problems POPULATION STRUCTURES Niching methods Speciation methods Island (migration) models: evolutionary algorithms based on punctuated equilibria Diffusion (cellular) models ADVANCED TECHNIQUES IN EVOLUTIONARY COMPUTATION Population sizing Mutation parameters Recombination parameters Parameter control Self-adaptation Meta-evolutionary approaches Coevolutionary algorithms IMPLEMENTATION OF EVOLUTIONARY ALGORITHMS Efficient implementation of algorithms Computation time of evolutionary operators Hardware realizations of evolutionary algorithms INDEX

Editorial Reviews

"This second volume provides very interesting information and updated material on additional topics. It also covers some advanced techniques and discusses the efficient implementation of evolutionary algorithms."
-H.D. Hecker, Zentralblatt Math

From the Publisher