Self-Adaptive Heuristics for Evolutionary Computation (Studies in Computational Intelligence)

Description:

keywords:bachelor of science computer science,of computer science,of computer science,of computer science,be computer science,

Evolutionary algorithms are successful biologically inspired meta-heuristics. Their success depends on adequate parameter settings. The question arises: how can evolutionary algorithms learn parameters automatically during the optimization? Evolution strategies gave an answer decades ago: self-adaptation. Their self-adaptive mutation control turned out to be exceptionally successful. But nevertheless self-adaptation has not achieved the attention it deserves.

This book introduces various types of self-adaptive parameters for evolutionary computation. Biased mutation for evolution strategies is useful for constrained search spaces. Self-adaptive inversion mutation accelerates the search on combinatorial TSP-like problems. After the analysis of self-adaptive crossover operators the book concentrates on premature convergence of self-adaptive mutation control at the constraint boundary. Besides extensive experiments, statistical tests and some theoretical investigations enrich the analysis of the proposed concepts.

keywords:bachelor of science computer science,of computer science,of computer science,of computer science,be computer science,

./upload/Computer%20Science/Self-Adaptive_Heuristics_for_E_9_6_2017_8_56_38_PM.jpg
eBook Details:
Category: Computer Science
Author: Oliver Kramer
Language: English
ISBN10: 3540692800
ISBN13:
Pages: 182
PubDate: 2008-00-00 00:00:00
UploadDate: 9/6/2017 8:56:38 pm

The Latest Upload

The Most Related

Category