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Soft Computing

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01.11.2015 | Methodologies and Application

Heterozygous differential evolution with Taguchi local search

verfasst von: Hu Peng, Zhijian Wu

Erschienen in: Soft Computing | Ausgabe 11/2015

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Abstract

Differential evolution (DE) is one of the most popular and powerful evolutionary algorithms for the real-parameter global continuous optimization problems. However, how to balance the exploration and exploitation is harder work to the researchers improving the performance of DE. Very often, we catch one and lose another. To overcome this problem, this paper presents a novel DE variant, called heterozygous DE with Taguchi local search (THDE), in which two new proposed methods (i.e., multiple schemes heterozygous evolution and Taguchi local search) are employed, with one as enhanced exploration ability and the other enhanced exploitation ability. The experimental studies have been conducted on 27 well-known test functions, including unimodal, multimodal and shifted test functions. Experimental results have verified the quality and effectiveness of THDE. Comparison with the state-of-the-art DE variants has proved that THDE is a type of new competitive algorithm.

Vorheriger Artikel A modified strategy of fuzzy clustering algorithm for image segmentation

Nächster Artikel Ostrowski type inequalities and applications in numerical integration for interval-valued functions

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Titel: Heterozygous differential evolution with Taguchi local search
verfasst von: Hu Peng
Zhijian Wu
Publikationsdatum: 01.11.2015
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 11/2015
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-014-1482-7

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