Title: Two-stage eagle strategy with differential evolution

Authors: Xin-She Yang; Suash Deb

Addresses: 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

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.

Keywords: bat algorithm; cuckoo search; eagle strategy; bio-inspired computation; differential evolution; global optimisation; pressure vessel design; speed reducer design.

DOI: 10.1504/IJBIC.2012.044932

International Journal of Bio-Inspired Computation, 2012 Vol.4 No.1, pp.1 - 5

Received: 08 Oct 2011
Accepted: 09 Oct 2011
Published online: 22 Sep 2014 *

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