2013 | OriginalPaper | Buchkapitel
Particle Swarm Optimization with Transition Probability for Timetabling Problems
verfasst von : Hitoshi Kanoh, Satoshi Chen
Erschienen in: Adaptive and Natural Computing Algorithms
Verlag: Springer Berlin Heidelberg
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In this paper, we propose a new algorithm to solve university course timetabling problems using a Particle Swarm Optimization (PSO). PSOs are being increasingly applied to obtain near-optimal solutions to many numerical optimization problems. However, it is also being increasingly realized that PSOs do not solve constraint satisfaction problems as well as other meta-heuristics do. In this paper, we introduce transition probability into PSO to settle this problem. Experiments using timetables of the University of Tsukuba showed that this approach is a more effective solution than an Evolution Strategy.