Abstract
Particle Swarm Optimization (PSO) is a swarm intelligence based numerical optimization algorithm, introduced in 1995 by James Kennedy, a social psychologist, and Russell Eberhart, an electrical engineer. PSO has been improved in many ways since its inception. This chapter provides an introduction to the basic particle swarm optimization algorithm. For better understanding of the algorithm, a worked-out example has also been given.
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Bansal, J.C., Deep, K.: A modified binary particle swarm optimization for knapsack problems. Appl. Math. Comput. 218(22), 11042–11061 (2012)
Delice, Y., Aydoğan, E.K., Özcan, U., İlkay, M.S.: Balancing two-sided u-type assembly lines using modified particle swarm optimization algorithm. 4OR 15(1), 37–66 (2017)
Engelbrecht, A.P.: Computational Intelligence: An Introduction. Wiley.com (2007)
Feng, J., Tian, F., Jia, P., He, Q., Shen, Y., Fan, S.: Improving the performance of electronic nose for wound infection detection using orthogonal signal correction and particle swarm optimization. Sens. Rev. 34(4), 389–395 (2014)
Indu, J., Jain, V.K., Jain, R.: Correlation feature selection based improved-binary particle swarm optimization for gene selection and cancer classification. Appl. Soft Comput. 62, 203–215 (2018)
James, K., Russell, E.: Particle swarm optimization. In Proceedings of 1995 IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)
Mataric, M.J.: Interaction and intelligent behavior. Technical report, DTIC Document (1994)
Mousavi, S.M., Bahreininejad, A., Nurmaya Musa, S., Yusof, F.: A modified particle swarm optimization for solving the integrated location and inventory control problems in a two-echelon supply chain network. J. Intell. Manuf. 28(1), 191–206 (2017)
Trelea, I.O.: The particle swarm optimization algorithm: convergence analysis and parameter selection. Inf. Process. Lett. 85(6), 317–325 (2003)
Webpage. http://birding.about.com/od/birdbehavior/a/why-birds-flock.htm
Wilson, E.: 0.(1975) Sociobiology: The New Synthesis (1980)
Yang, B.: Modified particle swarm optimizers and their application to robust design and structural optimization. Ph.D. thesis, Munchen, Technical University, Dissertation (2009)
Zhan, Z.-H., Xiao, J., Zhang, J., Chen, W.: Adaptive control of acceleration coefficients for particle swarm optimization based on clustering analysis. In: IEEE Congress on Evolutionary Computation, 2007. CEC 2007, pp. 3276–3282. IEEE (2007)
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Bansal, J.C. (2019). Particle Swarm Optimization. In: Bansal, J., Singh, P., Pal, N. (eds) Evolutionary and Swarm Intelligence Algorithms. Studies in Computational Intelligence, vol 779. Springer, Cham. https://doi.org/10.1007/978-3-319-91341-4_2
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DOI: https://doi.org/10.1007/978-3-319-91341-4_2
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