Fixed vs. self-adaptive crossover first differential evolution

Teo, Jason Tze Wi and Asni Tahir, and Norhayati Daut, and Nordaliela Mohd Rusli, and Norazlina Khamis, (2016) Fixed vs. self-adaptive crossover first differential evolution. Applied Mathematical Sciences, 10 (32). pp. 1603-1610. ISSN 1312-885X

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Abstract

Although the Differential Evolution (DE) algorithm is a powerful and commonly used stochastic evolutionary-based optimizer for solving non-linear, continuous optimization problems, it has a highly unconventional order of genetic operations when compared against canonical evolutionary-based optimizers whereby in DE, mutation is conducted first before crossover. This has led us to investigate both a fixed as well as self-adaptive crossover-first version of DE, of which the fixed version has yielded statistically significant improvements to its performance when solving two particular classes of continuous optimization problems. The self-adaptive version of this crossover-first DE was also observed to be producing optimization results which were superior than the conventional DE

Item Type: Article
Uncontrolled Keywords: Evolutionary Optimization Algorithms; Differential Evolution; Global Non-Linear Optimization; Self-Adaptation; CEC 2005 Benchmark
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: FACULTY > Faculty of Computing and Informatics
Depositing User: Unnamed user with email storage.bpmlib@ums.edu.my
Date Deposited: 31 Jan 2017 06:34
Last Modified: 25 Oct 2017 06:46
URI: http://eprints.ums.edu.my/id/eprint/15424

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