Firefly Algorithm for optimization problems with non-continuous variables: A Review and Analysis

TL;DR

This paper reviews modifications of the firefly algorithm tailored for optimization problems with non-continuous variables, discussing their strengths, weaknesses, and future research directions.

Contribution

It provides a comprehensive review of how the firefly algorithm has been adapted for non-continuous variables, highlighting key modifications and insights.

Findings

Effective for binary and integer problems

Identifies strengths and weaknesses of modifications

Suggests directions for future research

Abstract

Firefly algorithm is a swarm based metaheuristic algorithm inspired by the flashing behavior of fireflies. It is an effective and an easy to implement algorithm. It has been tested on different problems from different disciplines and found to be effective. Even though the algorithm is proposed for optimization problems with continuous variables, it has been modified and used for problems with non-continuous variables, including binary and integer valued problems. In this paper a detailed review of this modifications of firefly algorithm for problems with non-continuous variables will be discussed. The strength and weakness of the modifications along with possible future works will be presented.