A Customized Differential Evolutionary Algorithm for Bounded Constrained Optimization Problems

Wali Khan Mashwani, Zia Ur Rehman, Maharani A. Bakar, Ismail Koçak, Muhammad Fayaz and Atif Khan

Complexity, 2021, vol. 2021, 1-24

Abstract: Bound-constrained optimization has wide applications in science and engineering. In the last two decades, various evolutionary algorithms (EAs) were developed under the umbrella of evolutionary computation for solving various bound-constrained benchmark functions and various real-world problems. In general, the developed evolutionary algorithms (EAs) belong to nature-inspired algorithms (NIAs) and swarm intelligence (SI) paradigms. Differential evolutionary algorithm is one of the most popular and well-known EAs and has secured top ranks in most of the EA competitions in the special session of the IEEE Congress on Evolutionary Computation. In this paper, a customized differential evolutionary algorithm is suggested and applied on twenty-nine large-scale bound-constrained benchmark functions. The suggested C-DE algorithm has obtained promising numerical results in its 51 independent runs of simulations. Most of the 2013 IEEE-CEC benchmark functions are tackled efficiently in terms of proximity and diversity.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:5515701

DOI: 10.1155/2021/5515701

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