Combining landscape approximation and local search in global optimization

Ko-Hsin LIANG; Xin YAO; Charles NEWTON

doi:10.1109/CEC.1999.782663

Combining landscape approximation and local search in global optimization

Ko-Hsin LIANG
, Xin YAO
, Charles NEWTON

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

37 Citations (SciVal)

Abstract

Local search techniques have been applied in variant global optimization methods. The effect of local search to the function landscape can make multimodal problems easier to solve. For evolutionary algorithms, the usage of the step size control concept normally will result in failure by the individual to escape from the local optima during the final stage. We propose an algorithm combining landscape approximation and local search (LALS) which is designed to tackle those difficult multimodal problems. We demonstrate that LALS can solve problems with very rough landscapes and also that LALS has very good global reliability. © 1999 IEEE.

Original language	English
Title of host publication	Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999
Publisher	IEEE Computer Society
Pages	1514-1520
Number of pages	7
Volume	2
DOIs	https://doi.org/10.1109/CEC.1999.782663
Publication status	Published - 20 Jan 2003
Externally published	Yes

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10.1109/CEC.1999.782663

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Combining landscape approximation and local search in global optimization. / LIANG, Ko-Hsin; YAO, Xin; NEWTON, Charles.
Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999. Vol. 2 IEEE Computer Society, 2003. p. 1514-1520 782663.

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

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AU - YAO, Xin

AU - NEWTON, Charles

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N2 - Local search techniques have been applied in variant global optimization methods. The effect of local search to the function landscape can make multimodal problems easier to solve. For evolutionary algorithms, the usage of the step size control concept normally will result in failure by the individual to escape from the local optima during the final stage. We propose an algorithm combining landscape approximation and local search (LALS) which is designed to tackle those difficult multimodal problems. We demonstrate that LALS can solve problems with very rough landscapes and also that LALS has very good global reliability. © 1999 IEEE.

AB - Local search techniques have been applied in variant global optimization methods. The effect of local search to the function landscape can make multimodal problems easier to solve. For evolutionary algorithms, the usage of the step size control concept normally will result in failure by the individual to escape from the local optima during the final stage. We propose an algorithm combining landscape approximation and local search (LALS) which is designed to tackle those difficult multimodal problems. We demonstrate that LALS can solve problems with very rough landscapes and also that LALS has very good global reliability. © 1999 IEEE.

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BT - Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999

PB - IEEE Computer Society

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Combining landscape approximation and local search in global optimization

Abstract

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