Abstract
Based on our previously proposed Quantum-behaved Particle Swarm Optimization (QPSO), this paper discusses the applicability of QPSO to integer programming. QPSO is a global convergent search method, while the original Particle Swarm (PSO) cannot be guaranteed to find out the optima solution of the problem at hand. The application of QPSO to integer programming is the first attempt of the new algorithm to discrete optimization problem. After introduction of PSO and detailed description of QPSO, we propose a method of using QPSO to solve integer programming. Some benchmark problems are employed to test QPSO as well as PSO for performance comparison. The experiment results show the superiority of QPSO to PSO on the problems.
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Liu, J., Sun, J., Xu, W. (2006). Quantum-Behaved Particle Swarm Optimization for Integer Programming. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893257_114
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DOI: https://doi.org/10.1007/11893257_114
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46481-5
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