Improvement of Firefly Algorithm using Particle Swarm Optimization and Gravitational Search Algorithm
Subject Areas : Cloud computing
1 - University of Birjand
Keywords: Kbest Attractive Firefly, Global and Local Best Position, Gravitational Search Algorithm(GSA), Improved Firefly Algorithm (IFA), Movement in Algorithm, Particle Swarm Optimization.,
Abstract :
Evolutionary algorithms are among the most powerful algorithms for optimization, Firefly algorithm (FA) is one of them that inspired by nature. It is an easily implementable, robust, simple and flexible technique. On the other hand, Integration of this algorithm with other algorithms, can be improved the performance of FA. Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) are suitable and effective for integration with FA. Some method and operation in GSA and PSO can help to FA for fast and smart searching. In one version of the Gravitational Search Algorithm (GSA), selecting the K-best particles with bigger mass, and examining its effect on other masses has a great help for achieving the faster and more accurate in optimal answer. As well as, in Particle Swarm Optimization (PSO), the candidate answers for solving optimization problem, are guided by local best position and global best position to achieving optimal answer. These operators and their combination with the firefly algorithm (FA) can improve the performance of the search algorithm. This paper intends to provide models for improvement firefly algorithm using GSA and PSO operation. For this purpose, 5 scenarios are defined and then, their models are simulated using MATLAB software. Finally, by reviewing the results, It is shown that the performance of introduced models are better than the standard firefly algorithm.
[1]. N. Bacanin, M. Tuba, "Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Optimization Problem with Entropy Diversity Constraint", Scientific World Journal, Vol. 2014, P.P. 1-16, May 2014.
[2]. W.W. Hwu, "GPU Computing Gems Jade Edition", Morgan Kaufmann press, 2011.
[3]. X.S. Yang, "Nature-Inspired Metaheuristic Algorithms", Luniver Press. 2008.
[4]. N. F. Johari, A. M. Zain, N.H. Mustaffa, A. Udin, "Firefly Algorithm for Optimization Problem", Applied Mechanics and Materials, Vol. 421, P.P. 512-517, 2013.
[5]. A.H. Damia, M. Esnaashari, "Automated Test Data Generation Using a Combination of Firefly Algorithm and Asexual Reproduction Optimization Algorithm", International Journal of Web Research, Vol. 3, No. 1, P.P. 19-28, Spring-Summer, 2020.
[6]. I. Brajević, P.S. Stanimirović, S. Li, X. Cao, "A Hybrid Firefly and Multi-Strategy Artificial Bee Colony Algorithm", International Journal of Computational Intelligence Systems, Vol. 13, P.P. 810-821, 2020.
[7]. F. Wahid1, M. Sultan zia, R.N. Bin Rais, M. AAmir, U. Muneer butt, M. Ali, A. Ahmed, I. Ali khan, O. KHalid, "An Enhanced Firefly Algorithm Using Pattern Search for Solving Optimization Problems", IEEE Access, Vol. 8, P.P. 148264-148288, 2020.
[8]. W. Alomoush, K. Omar, A. Alrosan, Y. M. Alomari, D. Albashish, A. Almomani, "Firefly photinus search algorithm", Journal of King Saud University – Computer and Information Sciences, Vol. 32, P.P. 599–607, 2020.
[9]. SH. Mashhadi Farahani, A.A. Abshouri, B. Nasiri, M.R. Meybodi, "Some Hybrid Models to Improve Firefly Algorithm Performance", International Journal of Artificial Intelligence, Vol. 8, P.P. 1-20, 2012.
[10]. G.G. Wang, L. Guo, H. Duan, H. Wang, "A New Improved Firefly Algorithm for Global Numerical Optimization", Journal of Computational and Theoretical Nanoscience, Vol. 11, P.P. 477–485, 2014.
[11]. F. Wahid, R. Ghazali, L.H. Ismail, "Improved Firefly Algorithm Based on Genetic Algorithm Operators for Energy Efficiency in Smart Buildings", Arabian Journal for Science and Engineering, Vol. 44, P.P. 4027-4047, 2019.
[12]. J. Nayak, B. Naik, P. Dinesh, K. Vakula, P.B. Dash, "Firefly Algorithm in Biomedical and Health Care: Advances, Issues and Challenges", SN Computer Science. Vol. 1, P.P. 1-36, 2020.
[13]. H. Zhang, J Yang, J. Zhang, P. Song, X. Xu, "A Firefly Algorithm Optimization-Based Equivalent Consumption Minimization Strategy for Fuel Cell Hybrid Light Rail Vehicle", Energies, Vol. 12, P.P. 1-18, 2019.
[14]. M. Zile, "Routine Test Analysis in Power Transformers by Using Firefly Algorithm and Computer Program", IEEE Access, Vol. 8, P.P. 132033-132040, 2019.
[15]. S.P. Mishra, P.K. Dash, "Short-term prediction of wind power using a hybrid pseudo-inverse Legendre neural network and adaptive firefly algorithm", Neural Computing and Applications, Vol. 31, P.P. 2243–2268, 2019.
[16]. X.S. Yang, "Firefly Algorithm for Multimodal Optimization", SAGA 2009, Lecture Notes in Computer Science, Vol. 5792, P.P. 169-178, 2009.
[17]. Rashedi, “Gravitational search algorithm,” M.Sc. thesis, Dept. Elect. Eng., Shahid Bahonar University of Kerman, Kerman, Iran, 2007.
[18]. E. Rashedi, H. Nezamabadi-Pour, S. Saryazdi, "GSA: A gravitational search algorithm,” Information Science, Vol. 179, P.P. 2232-2248, June 2009.
[19]. P. Tharawetcharak, T. Karot, C. Pornsing, "An Improved Gravitational Coefficient Function for Enhancing Gravitational Search Algorithm’s Performance", International Journal of Machine Learning and Computing, Vol. 9, P.P. 261-266, June 2019.
[20]. R.C. Eberhart, J. Kennedy, "A new optimizer using particle swarm theory", Proceedings of the Sixth International Symposium on Micromachine and Human Science, Nagoya, Japan, P.P. 39–43, 1995.
[21]. J. Kennedy, R.C. Eberhart, "Particle swarm optimization", in Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ, P.P. 1942–1948, 1995.
[22]. Y. Jiang, T. Hu, C.C. Huang, X. Wu, "An improved particle swarm optimization algorithm", Applied Mathematics and Computation, Vol. 193, P.P. 231–239, 2007.
[23]. X. Yao, Y. Liu, G. Lin, "Evolutionary Programming Made Faster", IEEE Transactions on Evolutionary Computation, Vol. 3, No. 2, P.P. 82-102, 1999.
