A Customized Differential Evolutionary Algorithm for Bounded Constrained Optimization Problems. (10th March 2021)

• Record Type: Journal Article
• Authors: Mashwani, Wali Khan; Rehman, Zia Ur; Bakar, Maharani A.; Koçak, Ismail; Fayaz, Muhammad
• Other Names: Khan Atif Academic Editor.
• Is Part Of: Complexity. Volume 2021(2021)
• Publication Date: 2021-03-10
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2021/5515701
• Languages: English
• ISSNs: 1076-2787

Abstract

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.