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
Author(s)
Detail(s)
Original language | English |
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Title of host publication | Proceedings of the IEEE Conference on Evolutionary Computation |
Pages | 378-383 |
Volume | 1 |
Publication status | Published - 1995 |
Externally published | Yes |
Publication series
Name | |
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Volume | 1 |
Conference
Title | 1995 IEEE International Conference on Evolutionary Computation |
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Place | Australia |
City | Perth |
Period | 29 November - 1 December 1995 |
Link(s)
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