Paper Title:
A Hybrid Differential Evolution Algorithm for Solving Function Optimization
  Abstract

One of the key points resulting in the success of differential evolution (DE) is its mechanism of different mutation strategies for generating mutant vectors. In this paper, we also present a novel mutation strategy inspired by the velocity updating scheme of particle swarm optimization (PSO). The proposed approach is called HDE, which conducts the mutation strategy on the global best vector for each generation. Experimental studies on 8 well-known benchmark functions show that HDE outperforms other three compared DE algorithms in most test cases.

  Info
Periodical
Key Engineering Materials (Volumes 439-440)
Edited by
Yanwen Wu
Pages
315-320
DOI
10.4028/www.scientific.net/KEM.439-440.315
Citation
Z. G. Zhou, "A Hybrid Differential Evolution Algorithm for Solving Function Optimization", Key Engineering Materials, Vols. 439-440, pp. 315-320, 2010
Online since
June 2010
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Price
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