基于闪电的自然启发启发式优化算法

H. Shareef, M. Islam, A. A. Ibrahim, A. H. Mutlag
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引用次数: 7

摘要

提出了一种基于闪电过程的自然启发式优化算法——闪电搜索算法(LSA)来解决优化问题。它是利用快粒子理论推导出闪电的自然现象和阶跃引线传播过程。建立了三种粒子类型来描述产生第一步领导者群体的过渡粒子、试图成为领导者的空间粒子和代表从最佳位置的步骤领导者激发的粒子的先导粒子。为了验证建议算法的正确性和效率,使用具有几个特征的10个常用基准函数来验证LSA。并与其他两种已建立的方法进行了对比研究,以确认和比较LSA的性能。结果表明,与其他实验方法相比,LSA通常具有更好的结果,具有较高的收敛速度。
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A Nature Inspired Heuristic Optimization Algorithm Based on Lightning
This paper presents a nature inspired heuristic optimization algorithm based on lightning process called the lightning search algorithm (LSA) to solve optimization problems. It is derived from the natural phenomenon of lightning and the process of step leader propagation using the theory of fast particles. Three particle types are established to characterize the transition particles that generate the first step leader population, the space particles that try to become the leader, and the lead particle that represent the particle excited from best positioned step leader. To access the correctness and efficiency of the suggested algorithm, the LSA is verified using a well-used 10 benchmark functions with several characteristics. A comparative study with two other established methods is conducted to confirm and compare the performance of the LSA. The result exhibits that the LSA usually delivers better results compared with the other experimented methods with a high convergence rate.
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