NEFeb 25, 2016

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

arXiv:1602.07884v14 citations
AI Analysis

This is an incremental review for researchers in optimization and metaheuristics, focusing on adapting an existing algorithm to handle non-continuous variables.

The paper reviews modifications of the Firefly Algorithm for optimization problems with non-continuous variables, such as binary and integer-valued problems, analyzing their strengths and weaknesses.

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.

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