Two-stage eagle strategy with differential evolution
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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.
(from publisher's website)
|Keywords (uncontrolled):||bat algorithm; cuckoo search; eagle strategy; bio-inspired computation; differential evolution; global optimisation; pressure vessel design; speed reducer design.|
|Research Areas:||A. > School of Science and Technology > Design Engineering and Mathematics|
|Depositing User:||Teddy ~|
|Date Deposited:||15 Nov 2012 14:45|
|Last Modified:||13 Oct 2016 14:25|
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