Journal Article10.1016/J.ASOC.2015.07.028
Lightning search algorithm
Hussain Shareef,Ahmad Asrul Ibrahim,Ammar Hussein Mutlag +2 more
- 01 Nov 2015
- Vol. 36, pp 315-333
383
TL;DR: A novel metaheuristic optimization method called the lightning search algorithm (LSA) to solve constraint optimization problems based on the natural phenomenon of lightning and the mechanism of step leader propagation using the concept of fast particles known as projectiles.
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Abstract: Totally new optimization method inspired by lightning phenomena is introduced.The concept of projectiles and channel forking is adopted for movement of step leaders.Three types of projectiles are modeled as search mechanisms of LSA.The result of the LSA provides better results compared with the other tested methods. 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.
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