Firefly algorithm: overview, applications, and modifications
The Firefly Algorithm (FA) is a nature-inspired, population-based metaheuristic developed by Xin-She Yang in 2007 that mimics the flashing behavior of fireflies. This paper presents an in-depth investigation of the Firefly Algorithm, beginning with its biological inspiration and mathematical formulation, and proceeding to a comprehensive discussion of its diverse applications across engineering, image segmentation, scheduling, and other domains. In addition, various modifications of the original FA including Gaussian variants, chaotic variants, and opposition- and dimensional-based improvements are reviewed and compared. Two detailed tables summarize the primary applications and modifications, respectively, while discussions highlight the trade-offs between exploration and exploitation inherent in the algorithm. The paper concludes with an analysis of current achievements and future research directions in firefly-based optimization techniques.
Authors
- Renas Rajab Asaad (ORCID: https://orcid.org/0000-0002-1762-662X)
- Saman M. Almufti (ORCID: https://orcid.org/0000-0002-1843-745X)
- Awaz Ahmed Shaban (ORCID: https://orcid.org/0009-0003-5400-746X)
- Rasan Ismael Ali
Institutions
- Public Knowledge (US)
Publication Details
- Journal
- Journal of Image Processing and Intelligent Remote Sensing
- Published
- 2025-11-06
- DOI
- https://doi.org/10.55529/jipirs.52.1.16
- Primary Topic
- Metaheuristic Optimization Algorithms Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00