Lightning search algorithm

Hussain Shareef, Ahmad Asrul Ibrahim, Ammar Hussein Mutlag

Research output: Contribution to journalArticle

92 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)315-333
Number of pages19
JournalApplied Soft Computing Journal
Volume36
DOIs
Publication statusPublished - 23 Aug 2015
Externally publishedYes

Fingerprint

Lightning
Projectiles
Lead

Keywords

  • Benchmark functions
  • Constrained optimization
  • Lightning search algorithm
  • Nature-inspired algorithms

ASJC Scopus subject areas

  • Software

Cite this

Lightning search algorithm. / Shareef, Hussain; Ibrahim, Ahmad Asrul; Mutlag, Ammar Hussein.

In: Applied Soft Computing Journal, Vol. 36, 23.08.2015, p. 315-333.

Research output: Contribution to journalArticle

Shareef, Hussain ; Ibrahim, Ahmad Asrul ; Mutlag, Ammar Hussein. / Lightning search algorithm. In: Applied Soft Computing Journal. 2015 ; Vol. 36. pp. 315-333.
@article{11a03f8b9cf248718602d1b0547ef3d2,
title = "Lightning search algorithm",
abstract = "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.",
keywords = "Benchmark functions, Constrained optimization, Lightning search algorithm, Nature-inspired algorithms",
author = "Hussain Shareef and Ibrahim, {Ahmad Asrul} and Mutlag, {Ammar Hussein}",
year = "2015",
month = "8",
day = "23",
doi = "10.1016/j.asoc.2015.07.028",
language = "English",
volume = "36",
pages = "315--333",
journal = "Applied Soft Computing",
issn = "1568-4946",
publisher = "Elsevier BV",

}

TY - JOUR

T1 - Lightning search algorithm

AU - Shareef, Hussain

AU - Ibrahim, Ahmad Asrul

AU - Mutlag, Ammar Hussein

PY - 2015/8/23

Y1 - 2015/8/23

N2 - 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.

AB - 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.

KW - Benchmark functions

KW - Constrained optimization

KW - Lightning search algorithm

KW - Nature-inspired algorithms

UR - http://www.scopus.com/inward/record.url?scp=84939805523&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84939805523&partnerID=8YFLogxK

U2 - 10.1016/j.asoc.2015.07.028

DO - 10.1016/j.asoc.2015.07.028

M3 - Article

VL - 36

SP - 315

EP - 333

JO - Applied Soft Computing

JF - Applied Soft Computing

SN - 1568-4946

ER -