Improving local search in genetic algorithms for numerical global optimization using modified GRID-point search technique
Research output: Journal Publications and Reviews › RGC 22 - Publication in policy or professional journal
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 419-423 |
Journal / Publication | IEE Conference Publication |
Issue number | 414 |
Publication status | Published - 1995 |
Conference
Title | 1st International Conference on 'Genetic Algorithms in Engineering Systems: Innovations and Applications', GALESIA 1995 |
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Location | University of Sheffield |
Place | United Kingdom |
City | Sheffield |
Period | 12 - 14 September 1995 |
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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.
Citation Format(s)
Improving local search in genetic algorithms for numerical global optimization using modified GRID-point search technique. / Kwong, S.; Ng, A. Cl; Man, K. F.
In: IEE Conference Publication, No. 414, 1995, p. 419-423.
In: IEE Conference Publication, No. 414, 1995, p. 419-423.
Research output: Journal Publications and Reviews › RGC 22 - Publication in policy or professional journal