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

Research output: Journal Publications and ReviewsRGC 22 - Publication in policy or professional journal

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Original languageEnglish
Pages (from-to)419-423
Journal / PublicationIEE Conference Publication
Issue number414
Publication statusPublished - 1995


Title1st International Conference on 'Genetic Algorithms in Engineering Systems: Innovations and Applications', GALESIA 1995
LocationUniversity of Sheffield
PlaceUnited Kingdom
Period12 - 14 September 1995


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.