Coupled eagle strategy and differential evolution for unconstrained and constrained global optimization
Gandomi, Amir Hossein and Yang, Xin-She and Talatahari, Siamak (2012) Coupled eagle strategy and differential evolution for unconstrained and constrained global optimization. Computers & Mathematics with Applications, 63 (1). pp. 191-200. ISSN 0898-1221
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Official URL: http://dx.doi.org/10.1016/j.camwa.2011.11.010
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The performance of an optimization tool is largely determined by the efficiency of the search algorithm used in the process. The fundamental nature of a search algorithm will essentially determine its search efficiency and thus the types of problems it can solve. Modern metaheuristic algorithms are generally more suitable for globaloptimization. This paper carries out extensive globaloptimization of unconstrained and constrained problems using the recently developed eaglestrategy by Yang and Deb in combination with the efficient differentialevolution. After a detailed formulation and explanation of its implementation, the proposed algorithm is first verified using twenty unconstrainedoptimization problems or benchmarks. For the validation against constrained problems, this algorithm is subsequently applied to thirteen classical benchmarks and three benchmark engineering problems reported in the engineering literature. The performance of the proposed algorithm is further compared with various, state-of-the-art algorithms in the area. The optimal solutions obtained in this study are better than the best solutions obtained by the existing methods. The unique search features used in the proposed algorithm are analyzed, and their implications for future research are also discussed in detail.
|Keywords (uncontrolled):||Eagle strategy; Differential evolution; Unconstrained and constrained optimization; Global optimization; Benchmark|
|Research Areas:||A. > School of Science and Technology > Design Engineering and Mathematics|
|Deposited On:||16 Nov 2012 10:51|
|Last Modified:||27 Mar 2015 12:00|
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