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Lightning search algorithm: a comprehensive survey
Applied Intelligence ( IF 5.3 ) Pub Date : 2020-11-03 , DOI: 10.1007/s10489-020-01947-2
Laith Abualigah 1 , Mohamed Abd Elaziz 2, 3 , Abdelazim G Hussien 4 , Bisan Alsalibi 5 , Seyed Mohammad Jafar Jalali 6 , Amir H Gandomi 7
Affiliation  

The lightning search algorithm (LSA) is a novel meta-heuristic optimization method, which is proposed in 2015 to solve constraint optimization problems. This paper presents a comprehensive survey of the applications, variants, and results of the so-called LSA. In LSA, the best-obtained solution is defined to improve the effectiveness of the fitness function through the optimization process by finding the minimum or maximum costs to solve a specific problem. Meta-heuristics have grown the focus of researches in the optimization domain, because of the foundation of decision-making and assessment in addressing various optimization problems. A review of LSA variants is displayed in this paper, such as the basic, binary, modification, hybridization, improved, and others. Moreover, the classes of the LSA’s applications include the benchmark functions, machine learning applications, network applications, engineering applications, and others. Finally, the results of the LSA is compared with other optimization algorithms published in the literature. Presenting a survey and reviewing the LSA applications is the chief aim of this survey paper.



中文翻译:

闪电搜索算法:综合调查

闪电搜索算法(LSA)是一种新颖的元启发式优化方法,于 2015 年提出,用于解决约束优化问题。本文对所谓的 LSA 的应用、变体和结果进行了全面调查。在 LSA 中,最佳解决方案被定义为通过优化过程通过找到解决特定问题的最小或最大成本来提高适应度函数的有效性。元启发式算法已经成为优化领域研究的焦点,因为它是解决各种优化问题的决策和评估基础。本文展示了 LSA 变体的综述,例如基本的、二元的、修改的、杂交的、改进的等。此外,LSA 应用程序的类别包括基准功能,机器学习应用、网络应用、工程应用等。最后,将 LSA 的结果与文献中发表的其他优化算法进行了比较。提交调查和审查 LSA 申请是本调查文件的主要目的。

更新日期:2020-11-03
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