Population size reduction for the differential evolution algorithm

  • Authors:
  • Janez Brest;Mirjam Sepesy Maučec

  • Affiliations:
  • Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia;Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia

  • Venue:
  • Applied Intelligence
  • Year:
  • 2008

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Abstract

This paper studies the efficiency of a recently defined population-based direct global optimization method called Differential Evolution with self-adaptive control parameters. The original version uses fixed population size but a method for gradually reducing population size is proposed in this paper. It improves the efficiency and robustness of the algorithm and can be applied to any variant of a Differential Evolution algorithm. The proposed modification is tested on commonly used benchmark problems for unconstrained optimization and compared with other optimization methods such as Evolutionary Algorithms and Evolution Strategies.