Lightning search algorithm

被引:306
作者
Shareef, Hussain [1 ]
Ibrahim, Ahmad Asrul [1 ]
Mutlag, Ammar Hussein [1 ]
机构
[1] United Arab Emirates Univ, Dept Elect Engn, Al Ain, U Arab Emirates
关键词
Benchmark functions; Constrained optimization; Lightning search algorithm; Nature-inspired algorithms; DIFFERENTIAL EVOLUTION; OPTIMIZATION ALGORITHM; SWARM OPTIMIZATION; KRILL HERD; COLONY; BEHAVIOR; OPERATOR; DESIGN;
D O I
10.1016/j.asoc.2015.07.028
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper introduces a novel metaheuristic optimization method called the lightning search algorithm (LSA) to solve constraint optimization problems. It is based on the natural phenomenon of lightning and the mechanism of step leader propagation using the concept of fast particles known as projectiles. Three projectile types are developed to represent the transition projectiles that create the first step leader population, the space projectiles that attempt to become the leader, and the lead projectile that represent the projectile fired from best positioned step leader. In contrast to that of the counterparts of the LSA, the major exploration feature of the proposed algorithm is modeled using the exponential random behavior of space projectile and the concurrent formation of two leader tips at fork points using opposition theory. To evaluate the reliability and efficiency of the proposed algorithm, the LSA is tested using a well-utilized set of 24 benchmark functions with various characteristics necessary to evaluate a new algorithm. An extensive comparative study with four other well-known methods is conducted to validate and compare the performance of the LSA. The result demonstrates that the LSA generally provides better results compared with the other tested methods with a high convergence rate. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:315 / 333
页数:19
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