Abstract
Particle Swarm Optimization (PSO) is an evolutionary metaheuristic. It was created in 1995 by Kennedy and Eberhart for solving optimization problems. However, several alternatives to the original PSO algorithm have been proposed in the literature to improve its performance for solving continuous or discrete problems. We propose in this paper 4 classes of binary PSO algorithms (BPSO) for solving the NP-hard knapsack problem. In the proposed algorithms, the velocities and positions of particles are updated according to different equations. To verify the performance of the proposed algorithms, we made a comparison between algorithms of the 4 proposed classes and a comparison between the proposed algorithms with the Standard PSO2006 and the Standard BPSO. The comparison results showed that the proposed algorithms outperform the Standard PSO2006 and the Standard BPSO in terms of quality of solution found.
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References
Xie, X., Liu, J.: A Mini-Swarm for the quadratic Knapsack Problem. In: IEEE Swarm Intelligence Symposium (SIS), Honolulu, HI, USA, pp. 190–197 (2007)
Pisinger, D.: Where are the hard knapsack problems? Computers and Operations Research 32(9), 2271–2284 (2005)
Kennedy, J., Eberhart, R.C.: Particle Swarm Optimization. In: Proc. IEEE Int. Conf. On Neural Networks, WA, Australia, pp. 1942–1948 (1995)
Shi, Y., Eberhart, R.: Parameter Selection in Particle Swarm Optimisation. In: Proceedings of the 7th Annual Conference on Evolutionary Programming. LNCS, vol. 1447, pp. 591–600. Springer, Heidelberg (1998)
Wang, J., Zhou, Y.: Quantm-behaved Particle Swarm Optimization with Generalized Local Search Operator for Global Optimization. In: Advanced Intelligent Computing Theories and Applications With Aspects of Artificial Intelligence, pp. 851–860. Springer, Heidelberg (2007)
Gherboudj, A., Chikhi, S.: Algorithme d’OEPB pour Résoudre le Problème du Sac à Dos. In: Laouar, M.R. (ed.) Proceedings of the 1st International Conference on Information Systems and Technologies, ICIST 2011, Tebessa, Algeria, pp. 460–466 (2011) ISBN: 978-9931-9004-0-5
He, S., Wu, Q.H., Wen, J.Y., Saunders, J.R., Paton, R.: A Particle Swarm Optimizer with Passive Congregation. Biosystems, 135–147 (2004)
Zhong, W., Zhang, J., Chen, W.: A Novel Discrete Particle Swarm Optimization to Solve Traveling Salesman Problem. In: IEEE Congress on Evolutionary Computation, CEC 2007, pp. 3283–3287 (2007)
Clerc, M., Kennedy, J.: The Particle Swarm: Explosion, Stability, and Convergence in Multidimensional Complex Space. IEEE Transactions on Evolutionary Computation 6, 58–73 (2002)
Standard PSO2006, http://www.particleswarm.info/Programs.html
Kennedy, J., Eberhart, R.C.: A discrete binary version of the particle swarm algorithm. In: Proceedings of the World Multiconference on Systemics, Cybernetics and Informatics, Piscatawary, NJ, pp. 4104–4109 (1997)
Afshinmanesh, F., Marandi, A., Rahimi-Kian, A.: A novel binary particle swarm optimization method using artificial immune system. In: Proccedings of IEEE international conference on computer as a tool, pp. 217–220 (2005)
Liao, C., Tseng, C., Luarn, P.: A discrete version of particle swarm optimization for flowshop scheduling problems. Computers & Operations Research 34(10), 3099–3111 (2007)
Zhan, Z.-h., Zhang, J.: Discrete particle swarm optimization for multiple destination routing problems. In: Giacobini, M., Brabazon, A., Cagnoni, S., Di Caro, G.A., Ekárt, A., Esparcia-Alcázar, A.I., Farooq, M., Fink, A., Machado, P. (eds.) EvoWorkshops 2009. LNCS, vol. 5484, pp. 117–122. Springer, Heidelberg (2009)
Eberhart, R.C., Simpson, P., Dobbins, R.: Computational PC Tools, ch. 6, pp. 212-22, AP Professional (1996)
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Gherboudj, A., Chikhi, S. (2011). BPSO Algorithms for Knapsack Problem. In: Özcan, A., Zizka, J., Nagamalai, D. (eds) Recent Trends in Wireless and Mobile Networks. CoNeCo WiMo 2011 2011. Communications in Computer and Information Science, vol 162. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21937-5_20
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DOI: https://doi.org/10.1007/978-3-642-21937-5_20
Publisher Name: Springer, Berlin, Heidelberg
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