IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 8, No 3: September 2019

Performance comparison of various probability gate assisted binary lightning search algorithm

Md Mainul Islam (Western Sydney University)
Hussain Shareef (United Arab Emirates University)
Mahmood Nagrial (Western Sydney University)
Jamal Rizk (Western Sydney University)
Ali Hellany (Western Sydney University)
Saiful Nizam Khalid (Universiti Teknologi Malaysia)



Article Info

Publish Date
01 Sep 2019

Abstract

Recently, many new nature-inspired optimization algorithms have been introduced to further enhance the computational intelligence optimization algorithms. Among them, lightning search algorithm (LSA) is a recent heuristic optimization method for resolving continuous problems. It mimics the natural phenomenon of lightning to find out the global optimal solution around the search space. In this paper, a suitable technique to formulate binary version of lightning search algorithm (BLSA) is presented. Three common probability transfer functions, namely, logistic sigmoid, tangent hyperbolic sigmoid and quantum bit rotating gate are investigated to be utilized in the original LSA. The performances of three transfer functions based BLSA is evaluated using various standard functions with different features and the results are compared with other four famous heuristic optimization techniques. The comparative study clearly reveals that tangent hyperbolic transfer function is the most suitable function that can be utilized in the binary version of LSA.

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Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...