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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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
ID Code:15424
Deposited By:IR Admin
Deposited On:31 Jan 2017 14:34
Last Modified:31 Jan 2017 14:34

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