Abstract
To extend the existing PSO variants to their corresponding discrete versions, this paper presents a novel cyclic discrete optimization framework (CDOF) for particle swarm optimization. The proposed CDOF features the following characteristics. First, a general encoding method is proposed to describe the mapping relation between the PSO and the solution space. Second, a simple cyclic discrete rule is present to help the PSO to realize the extending from a continuous space to a discrete space. Two discrete PSO versions based on CDOF are tested on the traveling salesman problem comparing with each other. Experimental results show that the two discrete versions of the PSO algorithm based on CDOF are promising, and the framework is simple and effective for the PSO.
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Tao, Q., Chang, Hy., Yi, Y., Gu, Cq., Li, Wj. (2010). A Novel Cyclic Discrete Optimization Framework for Particle Swarm Optimization . In: Huang, DS., Zhao, Z., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Lecture Notes in Computer Science, vol 6215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14922-1_22
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DOI: https://doi.org/10.1007/978-3-642-14922-1_22
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