Lightning search algorithm: a comprehensive survey

Area of Science:

• Optimization Algorithms
• Meta-Heuristics
• Computational Intelligence

Background:

• Meta-heuristic optimization methods are increasingly researched for decision-making in complex problems.
• The lightning search algorithm (LSA), introduced in 2015, is a novel meta-heuristic approach.
• LSA aims to enhance fitness function effectiveness by identifying optimal solutions.

Purpose of the Study:

• To provide a comprehensive survey of the lightning search algorithm (LSA).
• To review the various applications, modifications, and performance results of LSA.
• To compare LSA's effectiveness against other optimization algorithms in the literature.

Main Methods:

• Literature review of LSA applications and variants.
• Categorization of LSA applications (benchmark functions, machine learning, networks, engineering).
• Analysis of different LSA modifications (basic, binary, hybrid, improved).

Main Results:

• LSA has demonstrated effectiveness across diverse optimization problems.
• Numerous variants of LSA have been developed to address specific challenges.
• Comparative studies show LSA's competitive performance against other algorithms.

Conclusions:

• LSA is a versatile and effective meta-heuristic optimization technique.
• The ongoing development of LSA variants expands its applicability.
• This survey highlights LSA's significance and potential in various scientific domains.