Two-Stage Eagle Strategy with Differential Evolution

Details Two-Stage Eagle Strategy with Differential Evolution Two-Stage Eagle Strategy with Differential Evolution

2012-03-29

arxiv.org/abs/1203.6586v1

Int. J. Bio-Inspired Computation, Vol. 4, No. 1, pp.1-5

Mathematics

Optimization and Control

Scientific paper

Efficiency of an optimization process is largely determined by the search algorithm and its fundamental characteristics. In a given optimization, a single type of algorithm is used in most applications. In this paper, we will investigate the Eagle Strategy recently developed for global optimization, 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 optimization problems such as pressure vessel and speed reducer design. Results suggest that we can reduce the computing effort by a factor of up to 10 in many applications.

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