Abstract
A comparative study is performed to reveal the convergence characteristics and the robustness of three local neighborhoods in the particle swarm optimization algorithm (PSO): ring, Von Neumann and singly-linked ring. In the PSO algorithm, a neighborhood enables different communication paths among its members, and therefore, the way the swarm searches the landscape. Since the neighborhood structure changes the flying pattern of the swarm, convergence and diversity differ from structure to structure. A set of controled experiments is developed to observe the transmission behavior (convergency) of every structure. The comparison results illustrate similarities and differences in the three topologies. A brief discussion is provided to further reveal the reasons which may account for the difference of the three neighborhoods.
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References
Bratton, D., Kennedy, J.: Defining a standard for particle swarm optimization. In: Proceedings of the IEEE Swarm Intelligence Symposium, pp. 120–127. IEEE (2007)
Clerc, M., Kennedy, J.: The particle swarm: explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation 6(1), 58–73 (2002)
Eberhart, R., Dobbins, R., Simpson, P.: Computational Intelligence PC Tools. Academic Press Professional (1996)
Hamdan, S.A.: Hybrid particle swarm optimiser using multi-neighborhood topologies. INFOCOMP Journal of Computer Science 7, 36–44 (2008)
De Jong, K.D.: An analysis of the behavior of a class of genetic adaptive systems. PhD thesis, Departament of Computer and Communication Sciences, University of Michigan, Ann Arbor, USA (1975)
Kennedy, J.: Small worlds and mega-minds: Effects of neighborhood topology on particle swarm performance. In: Proceedings of the IEEE Congress on Evolutionary Computation, pp. 1931–1938. IEEE (1999)
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of the IEEE International Conference on Neural Networks, pp. 1942–1948. IEEE (1995)
Kennedy, J., Eberhart, R.: The Particle Swarm: Social Adaptation in Information-Processing Systems. McGraw-Hill, London (1999)
Kennedy, J., Mendes, R.: Population structure and particle swarm performance. In: Proceedings of the 2002 Congress on Evolutionary Computation, pp. 1671–1676. IEEE (2002)
Kennedy, J., Mendes, R.: Neighborhood topologies in fully-informed and best-of-neighborhood particle swarms. IEEE Transaction on Systems, Man, and Cybernetics - Part C: Applications and Reviews 36(4), 515–519 (2006)
Kim, Y.H., Lee, K.H., Yoon, Y.: Visualizing the search process of particle swarm optimization. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 49–55. ACM (2009)
Mendes, R.: Population topologies and their influence in particle swarm performance. PhD thesis, Escola de Engenharia, Universidade do Minho (2004)
Mendes, R., Kennedy, J., Neves, J.: The fully informed particle swarm: Simpler, maybe better. IEEE Transactions on Evolutionary Computation 8(3), 204–210 (2004)
Mendes, R., Neves, J.: What Makes a Successful Society? Experiments with Population Topologies in Particle Swarms. In: Bazzan, A.L.C., Labidi, S. (eds.) SBIA 2004. LNCS (LNAI), vol. 3171, pp. 346–355. Springer, Heidelberg (2004)
Mohai, A., Mendes, R., Ward, C., Posthoff, C.: Neighborhood re-structuring in particle swarm optimization. In: Proceedings of the 18th Australian Joint Conference on Artificial Intelligence, pp. 776–785. Springer (2005)
Muñoz-Zavala, A.E., Hernández-Aguirre, A., Villa-Diharce, E.R.: The singly-linked ring topology for the particle swarm optimization algorithm. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 65–72. ACM (2009)
Ortiz-Boyer, D., Hervás-Martínez, C., García, N.: Cixl2: A crossover operator for evolutionary algorithms based on population features. Journal of Artificial Intelligence Research 24, 1–48 (2005)
Rastrigin, L.A.: Extremal control systems. Cybernetics Series. In: Theoretical Foundations of Engineering, Nauka, Russian (1974)
Safavieh, E., Gheibi, A., Abolghasemi, M., Mohades, A.: Particle swarm optimization with Voronoi neighborhood. In: Proceedings of the International CSI Computer Conference 2009, pp. 397–402. IEEE (2009)
Schwefel, H.P.: Numerical optimization of computer models. John Wiley and Sons, New York (1981)
Van den Bergh, F.: An analysis of particle swarm optimizers. PhD thesis, University of Pretoria, South Africa (2002)
Wolpert, D.H., Macready, W.G.: No free-lunch theorems for search. Technical report, Santa Fe Institute (1995)
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Muñoz Zavala, A.E. (2013). A Comparison Study of PSO Neighborhoods. In: Schütze, O., et al. EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II. Advances in Intelligent Systems and Computing, vol 175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31519-0_16
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DOI: https://doi.org/10.1007/978-3-642-31519-0_16
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