WSEAS Transactions on Systems and Control

Print ISSN: 1991-8763
E-ISSN: 2224-2856

Volume 12, 2017

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

Volume 12, 2017

A Novel Crossover-First Differential Evolution Algorithm with Explicitly Tunable Mutation Rates for Evolutionary-Based Global Optimization

AUTHORS: Jason Teo, Kim-On Chin, Shaliza Wahab, Azali Saudi, Siti Hasnah Tanalol

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ABSTRACT: Differential Evolution (DE) is currently one of the most popular evolutionary-based global optimization algorithms being simple to understand and implement as well as having fast convergence and robustness across a wide range of problems. Although it is classed as an evolutionary algorithm (EA), its genetic operations are atypical of such classes of algorithms. EAs typically perform crossover followed by mutation where both operations have an explicitly tunable rate of operation. However in DE, the mutation operation is conducted before the crossover operation. Moreover, although DE has a crossover rate, it does not have a mutation rate; rather it mandatorily mutates every gene in its chromosome essentially performing a 100% rate of mutation. Following this line of observation, we proceeded to experiment with a novel version of DE where the crossover and mutation operations are reversed to mimic typical EAs as well as to add in an explicitly tunable mutation rate. We have found that this simple and intuitive yet previously unexplored modification to DE is able to improve its performance, particularly in more complex search spaces with highly non-uniform fitness landscapes. Non-parametric tests show that the improvements are statistically significant

KEYWORDS: Global Optimization; Differential Evolution; Heuristic Search; Evolutionary Optimization; Genetic Operations.


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WSEAS Transactions on Systems and Control, ISSN / E-ISSN: 1991-8763 / 2224-2856, Volume 12, 2017, Art. #36, pp. 339-346

Copyright © 2017 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

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