Firefly Algorithms for Multimodal Optimization
Abstract
Nature-inspired algorithms are among the most powerful algorithms for optimization. This paper intends to provide a detailed description of a new Firefly Algorithm (FA) for multimodal optimization applications. We will compare the proposed firefly algorithm with other metaheuristic algorithms such as particle swarm optimization (PSO). Simulations and results indicate that the proposed firefly algorithm is superior to existing metaheuristic algorithms. Finally we will discuss its applications and implications for further research.
- Publication:
-
arXiv e-prints
- Pub Date:
- March 2010
- DOI:
- 10.48550/arXiv.1003.1466
- arXiv:
- arXiv:1003.1466
- Bibcode:
- 2010arXiv1003.1466Y
- Keywords:
-
- Mathematics - Optimization and Control;
- optimization and control
- E-Print:
- X.-S. Yang, Firefly algorithms for multimodal optimization, in: Stochastic Algorithms: Foundations and Applications, SAGA 2009, Lecture Notes in Computer Sciences, Vol. 5792, pp. 169-178 (2009).