Issue:Generalized net model of the Firefly algorithm

shortcut

http://ifigenia.org/wiki/issue:iwgn-14-22-27

Title of paper: Generalized net model of the Firefly algorithm Author(s): Olympia Roeva Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 “Acad. G. Bonchev” Str., Sofia–1113, Bulgaria olympia@biomed.bas.bg Pedro Melo-Pinto CETAV - University of Tras-os-Montes e Alto Douro, Ap. 1014, 5001-911 Vila Real, Portugal pmelo@utad.pt Presented at: 14th IWGN, Burgas, 29-30 November 2013 Published in: Conference proceedings, pages 22-27 Download:  PDF (158  Kb, File info) Abstract: The apparatus of generalized nets is herewith applied to describe the Firefly algorithm (FA). The FA is very efficient and can outperform other meta-heuristics, such as genetic algorithms, for solving many optimization problems. Although the FA has many similarities with other swarm intelligence based algorithms, such as Particle Swarm Optimization, Artificial Bee Colony Algorithm, and Bacterial Foraging Algorithm, it is indeed much simpler both in concept and implementation. The proposed generalized net model provides the opportunity to describe the logic of FA. Keywords: Generalized nets, Meta-heuristics, Firefly algorithm. AMS Classification: 65K10, 90C15, 90C31, 68Q85 References: Apostolopoulos, T., A. Vlachos, Application of the Firefly Algorithm for Solving the Economic Emissions Load Dispatch Problem, International Journal of Combinatorics, Article ID 523806, 2011. Atanassov, K., Generalized Nets and Systems Theory, Academic Publishing House “Prof. M. Drinov”, Sofia, 1997. Atanassov, K., Generalized Nets, World Scientific, Singapore, 1991. Atanassov K., On Generalized Nets Theory, “Prof. Marin Drinov” Acad. Publ. House, Sofia, 2007. Chai-ead, N., P. Aungkulanon, P. Luangpaiboon, Bees and Firefly Algorithms for Noisy Non-linear Optimisation Problems, Prof. Int. Multiconference of Engineers and Computer Scientists, 2, 2011, 1449–1454. Choy, E., M. Krawczak, A. Shannon, E. Szmidt (Eds.), A Survey of Generalized Nets, Raffles KvB Monograph No 10, Australia, 2007. Nasiri, B., M. R. Meybodi, Speciation-based Firefly Algorithm for Optimization in Dynamic Environments, Int. J. Artificial Intelligence, 8(S12), 2012, 118–132. Roeva, O. A. Shannon, T. Pencheva, Description of Simple Genetic Algorithm Modifications Using Generalized Nets, Proc. of 6th IEEE Int. Conf. Intelligent Systems 2012, Sofia, Bulgaria, Vol. 2, 2012, 178–183. Roeva, O., K. Atanassov, Generalized Net Model of a Modified Genetic Algorithm, Issues in Intuitionistic Fuzzy Sets and Generalized Nets, Wydawnictwo WSISiZ, Warszawa, 7, 2008, 93–99. Roeva, O., Optimization of E. coli Cultivation Model Parameters Using Firefly Algorithm, Int. J. Bioautomation, 16(1), 2012, 23–32. Roeva, O., T. Pencheva, Generalized Net Model of a Multi-population Genetic Algorithm, Issues in Intuitionistic Fuzzy Sets and Generalized Nets, Wydawnictwo WSISiZ, Warszawa, 8, 2010, 91–101. Roeva, O., Ts. Slavov, Firefly Algorithm Tuning of PID Controller for Glucose Concentration Control during E. coli Fed-batch Cultivation Process, Proceedings of the Federated Conference on Computer Science and Information Systems, WCO 2012, Poland, 455–462. Yang, X. S., Nature-inspired Meta-heuristic Algorithms, Luniver Press, Beckington, UK, 2008. Yang, X. S., Firefly Algorithm for Multimodal Optimization, Lecture Notes in Computing Sciences, 5792, 2009, 169–178. Yang, X. S., Firefly Algorithm, Levy Flights and Global Optimization, Research and Development in Intelligent Systems XXVI, Springer, London, UK, 2010, 209–218. Yang, X. S., Firefly Algorithm, Stochastic Test Functions and Design Optimisation, International Journal of Bio-inspired Computation, 2(2), 2010, 78–84. Yousif, A., A. H. Abdullah, S. M. Nor, A. A. Abdelaziz, Scheduling Jobs on Grid Computing using Firefly Algorithm, Journal of Theoretical and Applied Information Technology, 33(2), 2011, 155–164. Citations: The list of publications, citing this article may be empty or incomplete. If you can provide relevant data, please, write on the talk page.