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A new improved krill herd algorithm for global numerical optimization
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DOI：10.1016/j.neucom.2014.01.023.png)
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Abstract
En 中文
This study presents an improved krill herd (IKH) approach to solve global optimization problems. The main improvement pertains to the exchange of information between top krill during motion calculation process to generate better candidate solutions. Furthermore, the proposed IKH method uses a new Levy flight distribution and elitism scheme to update the KH motion calculation. This novel meta-heuristic approach can accelerate the global convergence speed while preserving the robustness of the basic KH algorithm. Besides, the detailed implementation procedure for the IKH method is described. Several standard benchmark functions are used to verify the efficiency of IKH. Based on the results, the performance of IKH is superior to or highly competitive with the standard KH and other robust population-based optimization methods. (C) 2014 Elsevier B.V. All rights reserved.
Keywords:
Global optimization problem
Krill herd
Exchange information
Multimodal function
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6.5
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2.5W
Citations:
6.5W
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