Complexity (Jan 2021)

A Customized Differential Evolutionary Algorithm for Bounded Constrained Optimization Problems

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

DOI
https://doi.org/10.1155/2021/5515701
Journal volume & issue
Vol. 2021

Abstract

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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.