Two-stage eagle strategy with differential evolution

  • Authors:

  • Xin-She Yang;Suash Deb

  • Affiliations:

  • Mathematics and Scientific Computing, National Physical Laboratory, Teddington TW11 0LW, UK.;Department of Computer Science and Engineering, C.V. Raman College of Engineering, Bidyanagar, Mahura, Janla, Bhubaneswar 752054, India

  • Venue:
  • International Journal of Bio-Inspired Computation
  • Year:
  • 2012

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Abstract

Efficiency of an optimisation process is largely determined by the search algorithm and its fundamental characteristics. In a given optimisation, a single type of algorithm is used in most applications. In this paper, we will investigate the eagle strategy recently developed for global optimisation, which uses a two-stage strategy by combing two different algorithms to improve the overall search efficiency. We will discuss this strategy with differential evolution and then evaluate their performance by solving real-world optimisation problems such as pressure vessel and speed reducer design. Results suggest that we can reduce the computing effort by a factor of up to ten in many applications.