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A Customized Differential Evolutionary Algorithm for Bounded Constrained Optimization Problems

Author

Listed:
  • Wali Khan Mashwani
  • Zia Ur Rehman
  • Maharani A. Bakar
  • Ismail Koçak
  • Muhammad Fayaz
  • Atif Khan

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.

Suggested Citation

  • Wali Khan Mashwani & Zia Ur Rehman & Maharani A. Bakar & Ismail Koçak & Muhammad Fayaz & Atif Khan, 2021. "A Customized Differential Evolutionary Algorithm for Bounded Constrained Optimization Problems," Complexity, Hindawi, vol. 2021, pages 1-24, March.
    • Handle: RePEc:hin:complx:5515701
    DOI: 10.1155/2021/5515701
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