改进的自私羊群优化器的功能优化

Int. J. Comput. Intell. Appl. Pub Date : 2020-03-01 DOI:10.1142/s1469026820500030

Ruxin Zhao, Yongli Wang, Chang Liu, Peng Hu, Yanchao Li, Hao Li, Chi Yuan

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引用次数: 1

摘要

自私群优化算法(SHO)是一种新的优化算法。然而，其优化性能并不令人满意。造成这种现象的主要原因是SHO的全局搜索能力较弱。在本文中，为了提高SHO的全局搜索能力，我们加入了Levy-flight分配策略。为了验证所提出算法的性能，我们使用了10个基准函数作为测试用例。实验结果表明，该算法具有较强的竞争力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Modified Selfish Herd Optimizer for Function Optimization

Selfish herd optimizer (SHO) is a new optimization algorithm. However, its optimization performance is not satisfactory. The main reason for this phenomenon is the weak global search ability of SHO. In this paper, in order to increase the global search ability of SHO, we add Levy-flight distribution strategy. To verify the performance of the proposed algorithm, we use 10 benchmark functions as test cases. Experiment results show that our algorithm is more competitive.

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Int. J. Comput. Intell. Appl.

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