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The Firefly Optimization Algorithm: Convergence Analysis and Parameter Selection
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 69 - Number 3 |
| Year of Publication: 2013 |
| Authors: Sankalap Arora, Satvir Singh |
10.5120/11826-7528
|
Sankalap Arora, Satvir Singh . The Firefly Optimization Algorithm: Convergence Analysis and Parameter Selection. International Journal of Computer Applications. 69, 3 ( May 2013), 48-52. DOI=10.5120/11826-7528
Abstract
The bio-inspired optimization techniques have obtained great attention in recent years due to its robustness, simplicity and efficiency to solve complex optimization problems. The firefly Optimization (FA or FFA) algorithm is an optimization method with these features. The algorithm is inspired by the flashing behavior of fireflies. In the algorithm, randomly generated solutions will be considered as fireflies, and brightness is assigned depending on their performance on the objective function. The algorithm is analyzed on basis of performance and success rate using five standard benchmark functions by which guidelines of parameter selection are derived. The tradeoff between exploration and exploitation is illustrated and discussed.
References
- Y. Liu and K. M. Passino, "Swarm Intelligence: A Survey", International Conference of Swarm Intelligence, 2005.
- X. S Yang, "Engineering Optimization: An introduction with metaheuristic Applications", Wiley & Sons, New Jersey, 2010.
- X. S. Yang, "Nature-Inspired Metaheuristic Algorithms", Luniver Press, 2008
- X. S. Yang, "Engineering Optimization: An Introduction with Metaheuristic Applications". Wiley & Sons, New Jersey, 2010.
- D. Yazdani, and M. R. Meybodi , "AFSA-LA: A New Model for Optimization", Proceedings of the 15th Annual CSI Computer Conference (CSICC'10), Feb. 20-22, 2010.
- D. E. Goldberg, "Genetic Algorithms in Search, Optimization and Machine Learning, Reading, Mass", Addison Wesley, 1989
- I. H. Holland, "Adaptation in natural and Artificial Systems", University of Michigan, Press, Ann Abor, 1975.
- J. Kennedy, R. C. Eberhart, "Particle swarm optimization", IEEE International Conference on Neural Networks, Piscataway, NJ. , pp. 942-1948, 1995.
- T. Baeck, D. B. Fogel and Z. Michalewicz, "Handbook of Evolutionary Computation", Taylor & Francis, 1997.
- J. Kennedy J. , R. Eberhart and Y. Shi, "Swarm intelligence", Academic Press, 2001
- F. Tangour and P. Borne,(2008) "Presentation of some Meta-heuristic for the Optimization of complex system", in: Studies in Informatics and Control, Vol. 17, No. 2,pp. 169-180
- L. X. Li, Z. J. Shao and J. X. Qian, "An optimizing Method based on Autonomous Animals: Fish Swarm Algoritm", System Engineering Theory & Practice, 2002.
- Wright JA, Farmani R (2001) Genetic algorithm: A fitness formulation for constrained minimization in Proc. of Genetic and Evolutionary Computation Conf. , San Francisco, CA, pp 725–732, 2011.
- S. L. ukasik and AK. SÃlawomirZ, "Firefly algorithm for Continuous Constrained Optimization Tasks", 1st International Confernce on Computational Collective Intelligence, Semantic Web, Social Networks and Multiagent Systems, Springer-Verlag Berlin, Heidelberg, pp. 169-178, 2009.
- K. Krishnand, K, Ghose, and D, "Glowworms swarm based optimization algorithm for multimodal functions with collective robotics applications", Int. J. of Multiagent and Grid Systems, Vol. 2, No. 3, pp. 209-222, 2006.
- X. -S Yang,(2009)"Firefly algorithms for multimodal optimization" in:Stochastic algorithms: Foundations and Applications,SAGA 2009, Lecture notes in computer sciences,Vol 5792,pp. 169-178
- X. -S Yang,(2010)"Firefly algorithm, L'evy flights and global optimization", in :Research and development in Intelligent Systems XXVI(Eds M. Bramer, R. Ellis, M. Petridis), Springer London,pp. 209-218
- T. Apostolopoulos and A. Vlachos, "Application of the firefly algorithm for solving the economic emissions load dispatch problem", in: International Journal of Coimbinatorics, Vol. 2011,pp. 1-23.
- H. banati and M. Bajaj, (2011),"Firefly based feature selection approach", IJCSI International Journal of Computer Science Issues, vol. 8,Issue 4, no. 2,pp. 473-480
- N. Chai-ead, P. Aungkulanon*, and P. Luangpaiboon, 2011, "Bees and firefly algorithms for noisy non-linear optimization problems", International Multiconference of engineers and scientists (IMECS), Vol. II, Hong Kong.
- B. G. Babu and M. Kannan, " Lightning bugs", Resonance, Vol. 7, No. 9, pp. 49-55, 2002.
- X. S. Yang, (2010). "Firefly Algorithm Stochastic Test Functions and Design Optimization". Int. J. Bio-Inspired Computation, vol. 2, No. 2, pp. 78-84, 2010.
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