Fixed vs. Self-Adaptive Crossover First Differential Evolution

Jason Teo 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). 1603 -1610.

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Although the Differential Evolution (DE) algorithm is a powerfuland commonly used stochastic evolutionary-based optimizer for solvingnon-linear, continuous optimization problems, it has a highly uncon-ventional order of genetic operations when compared against canonicalevolutionary-based optimizers whereby in DE, mutation is conductedfirst before crossover. This has led us to investigate both a fixed aswell as self-adaptive crossover-first version of DE, of which the fixedversion has yielded statistically significant improvements to its perfor-mance when solving two particular classes of continuous optimizationproblems. The self-adaptive version of this crossover-first DE was alsoobserved to be producing optimization results which were superior thanthe conventional DE.

Item Type: Article
Uncontrolled Keywords: Evolutionary Optimization Algorithms, Differential Evolution Global Non-Linear Optimization, Self-Adaptation, CEC 2005 Benchmark
Subjects: Q Science > QA Mathematics
Divisions: FACULTY > Faculty of Computing and Informatics
Depositing User: OTHMAN HJ RAWI -
Date Deposited: 08 Mar 2019 08:11
Last Modified: 11 Nov 2020 00:44

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