Introducing start expression genes to the linkage learning genetic algorithm

Ying-Ping Chen, David E. Goldberg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

This paper discusses the use of start expression genes and a modified exchange crossover operator in the linkage learning genetic algorithm (LLGA) that enables the genetic algorithm to learn the linkage of building blocks (BBs) through probabilistic expression (PE). The difficulty that the original LLGA encounters is shown with empirical results. Based on the observation, start expression genes and a modified exchange crossover operator are proposed to enhance the ability of the original LLGA to separate BBs and to improve LLGA’s performance on uniformly scaled problems. The effect of the modifications is also presented in the paper.

Original languageEnglish
Title of host publicationParallel Problem Solving from Nature - PPSN 2002 - 7th International Conference, Proceedings
EditorsPanagiotis Adamidis, Juan Julian Merelo Guervos, Hans-Georg Beyer, Hans-Paul Schwefel, Jose-Luis Fernandez-Villacanas
PublisherSpringer Verlag
Pages351-360
Number of pages10
ISBN (Print)3540441395
DOIs
StatePublished - 1 Jan 2002
Event7th International Conference on Parallel Problem Solving from Nature, PPSN 2002 - Granada, Spain
Duration: 7 Sep 200211 Sep 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2439
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Parallel Problem Solving from Nature, PPSN 2002
CountrySpain
CityGranada
Period7/09/0211/09/02

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