Performance comparison of various probability gate assisted binary lightning search algorithm

Md Mainul Islam, Hussain Shareef, Mahmood Nagrial, Jamal Rizk, Ali Hellany, Saiful Nizam Khalid

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)228-236
Number of pages9
JournalIAES International Journal of Artificial Intelligence
Issue number3
Publication statusPublished - 2019


  • Benchmark function
  • Binary lightning search algorithm
  • Decoding
  • Probability
  • Transfer functions

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems and Management
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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