TY - GEN
T1 - A nature inspired heuristic optimization algorithm based on lightning
AU - Shareef, Hussain
AU - Islam, Md Mainul
AU - Ibrahim, Ahmad Asrul
AU - Mutlag, Ammar Hussein
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/10/20
Y1 - 2016/10/20
N2 - 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.
AB - 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.
KW - Benchmark function
KW - lightning search algorithm
KW - nature-inspired algorithms
KW - optimization
UR - http://www.scopus.com/inward/record.url?scp=84997552924&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84997552924&partnerID=8YFLogxK
U2 - 10.1109/AIMS.2015.12
DO - 10.1109/AIMS.2015.12
M3 - Conference contribution
AN - SCOPUS:84997552924
T3 - Proceedings - AIMS 2015, 3rd International Conference on Artificial Intelligence, Modelling and Simulation
SP - 9
EP - 14
BT - Proceedings - AIMS 2015, 3rd International Conference on Artificial Intelligence, Modelling and Simulation
A2 - Hijazi, Mohd Hanafi Ahmad
A2 - Saad, Ismail
A2 - Al-Dabass, David
A2 - Bolong, Nurmin
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Artificial Intelligence, Modelling and Simulation, AIMS 2015
Y2 - 2 December 2015 through 4 December 2015
ER -