Accelerated genetic algorithms : combined with local search techniques for fast and accurate global search

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings of the IEEE Conference on Evolutionary Computation
Pages378-383
Volume1
Publication statusPublished - 1995
Externally publishedYes

Publication series

Name
Volume1

Conference

Title1995 IEEE International Conference on Evolutionary Computation
PlaceAustralia
CityPerth
Period29 November - 1 December 1995

Abstract

This paper discusses a combinatorial method to compute a global solution of a non-convex optimization problem. A hybrid algorithm is the synthesis of a genetic algorithm and a local search algorithm (e.g nonlinear programming). The hybrid algorithm is not only faster than the genetic algorithm but also gives a more accurate solution. In addition, the length of chromosome required is much smaller. An abstract analysis of the hybrid algorithm is discussed based on which a convergent proof of this algorithm is derived. Finally, simulations are performed to show the efficiency of the algorithm.

Citation Format(s)

Accelerated genetic algorithms : combined with local search techniques for fast and accurate global search. / Chak, Chu Kwong; Feng, Gang.

Proceedings of the IEEE Conference on Evolutionary Computation. Vol. 1 1995. p. 378-383.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review