Two improved differential evolution schemes for faster global search

  • Authors:
  • Swagatam Das;Amit Konar;Uday K. Chakraborty

  • Affiliations:
  • Jadavpur University, Kolkata, India;Jadavpur University, Kolkata, India;University of Missouri, St. Louis, MO

  • Venue:
  • GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
  • Year:
  • 2005

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Abstract

Differential evolution (DE) is well known as a simple and efficient scheme for global optimization over continuous spaces. In this paper we present two new, improved variants of DE. Performance comparisons of the two proposed methods are provided against (a) the original DE, (b) the canonical particle swarm optimization (PSO), and (c) two PSO-variants. The new DE-variants are shown to be statistically significantly better on a seven-function test bed for the following performance measures: solution quality, time to find the solution, frequency of finding the solution, and scalability.