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.
International Journal of Bio-Inspired Computation, 2012 Vol.4 No.1, pp.1 - 5
Available online: 16 Jan 2012 *Full-text access for editors Access for subscribers Purchase this article Comment on this article