Abstract
Nature-inspired algorithms are more relevant today, such as PSO and ACO, which have been used in several types of problems such as the optimization of neural networks, fuzzy systems, control, and others showing good results [1–5]. There are other methods that have been proposed more recently, the firefly algorithm is one of them, this paper will explain the algorithm and describe how it behaves. In this paper the firefly algorithm was applied in optimizing benchmark functions and comparing the results of the same functions with genetic algorithms.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning, Reading, Mass, Addison Wesley, Reading (1989)
Melendez, A., Castillo, O.: Evolutionary optimization of the fuzzy integrator in a navigation system for a mobile robot. Recent Adv. Hybrid Intell. Syst. 21–31 (2013)
Rodriguez Vázquez, K.: Multiobjective Evolutionary Algorithms in Non-linear System Identification. Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, p. 185 (1999)
Astudillo, L., Melin, P., Castillo, O.: Optimization of a fuzzy tracking controller for an autonomous mobile robot under perturbed torques by means of a chemical optimization paradigm. Recent Adv. Hybrid Intell. Syst. 3–20 (2013)
Cervantes, L., Castillo, O.: Genetic optimization of membership functions in modular fuzzy controllers for complex problems. Recent Adv Hybrid Intell. Syst. 51–62 (2013)
Holland, H.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor (1975)
Yang, X.S.: Nature-Inspired Metaheuristic Algorithms. Luniver Press, Europe (2008)
Yang, X.S.: Firefly algorithms for multimodal optimization. In: Stochastic Algorithms Foundations and Applications (SAGA’09). Lecture Notes in Computing Sciences, Vol. 5792. , Springer, New York, pp. 169–178 (2009)
Yang, X.S.: Firefly algorithm stochastic test functions and design optimization. Int. J. Bio-Inspired Comput. 2(2), 78–84 (2010)
Yang, X.S.: Firefly algorithm, lévy flights and global optimization. In: Bramer, M., Ellis, R., Petridis, M. (eds.) Research and Development in Intelligent Systems, Vol. XXVI, pp. 209–218. Springer, London (2010)
Valdez, F., Melin, P.: Comparative study of particle swarm optimization and genetic algorithms for mathematical complex functions. J. Autom. Mob. Robot. Intell. Syst. (JAMRIS) 2, 43–51 (2008)
Valdez, F., Melin, P., Castillo, O.: An improved evolutionary method with fuzzy logic for combining particle swarm optimization and genetic algorithms. Appl. Soft Comput. 11(2), 2625–2632 (2011)
Valdez, F., Melin, P., Castillo, O.: Bio-inspired optimization methods on graphic processing unit for minimization of complex mathematical functions. Recent Adv. Hybrid Intell. Syst. 313–322 (2013)
Melin, P., Olivas, F., Castillo, O., Valdez, F., Soria, J., García, J.M.: Valdez: optimal design of fuzzy classification systems using PSO with dynamic parameter adaptation through fuzzy logic. Expert Syst. Appl. 40(8), 3196–3206 (2013)
Haupt, R., Haupt, S.: Practical genetic algorithms 2nd ed. A Wiley-Interscience Publication (1998)
Solano-Aragon, C., Castillo, O.: Optimization of benchmark mathematical functions using the firefly algorithm. Recent Adv. Hybrid Approaches Designing Intell. Syst. 177–189 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Solano-Aragón, C., Castillo, O. (2015). Optimization of Benchmark Mathematical Functions Using the Firefly Algorithm with Dynamic Parameters. In: Castillo, O., Melin, P. (eds) Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics. Studies in Computational Intelligence, vol 574. Springer, Cham. https://doi.org/10.1007/978-3-319-10960-2_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-10960-2_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10959-6
Online ISBN: 978-3-319-10960-2
eBook Packages: EngineeringEngineering (R0)