Improving local search in genetic algorithms for numerical global optimization using modified GRID-point search technique

S. KWONG*, A. C. NG, K. F. MAN

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

8 Citations (Scopus)

Abstract

This paper presents a Hybrid system for numerical global optimization problems based on the Genetic Algorithms (GAs) and modified GRID-point search. Experimental results indicate that the Hybrid system outperforms the classical GAs as the modified GRID can (i) speed up the search, (ii) further improve the fine tuning capabilities of GAs, and (iii) overcome the premature termination. The Hybrid system not only improve the searching capabilities of classical GAs but it also preserves the randomization of the searching space. In addition, the effectiveness of the genetic operators is addressed in this paper.

Original languageEnglish
Title of host publicationProceedings of the 1st IEE/IEEE International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications
PublisherIET
Pages419-423
Number of pages5
ISBN (Print)0852966504
DOIs
Publication statusPublished - 1995
Externally publishedYes
Event1st IEE/IEEE International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, GALESIA '95 - Sheffield, United Kingdom
Duration: 12 Sept 199514 Sept 1995

Publication series

NameIEE Conference Publication
ISSN (Print)0537-9989

Conference

Conference1st IEE/IEEE International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, GALESIA '95
Country/TerritoryUnited Kingdom
CitySheffield
Period12/09/9514/09/95

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