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A Comparative Study of Modern Heuristics on the School Timetabling Problem

1
Department of Business Administration of Food and Agricultural Enterprises, University of Patras, G. Seferi 2, 30100 Agrinio, Greece
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School of Science and Technology, Hellenic Open University, Parodos Aristotelous 18, 26335 Patra, Greece
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Author to whom correspondence should be addressed.
Academic Editor: Tom Burr
Algorithms 2015, 8(3), 723-742; https://doi.org/10.3390/a8030723
Received: 17 July 2015 / Revised: 6 August 2015 / Accepted: 20 August 2015 / Published: 28 August 2015
In this contribution a comparative study of modern heuristics on the school timetabling problem is presented. More precisely, we investigate the application of two population-based algorithms, namely a Particle Swarm Optimization (PSO) and an Artificial Fish Swarm (AFS), on the high school timetabling problem. In order to demonstrate their efficiency and performance, experiments with real-world input data have been performed. Both algorithms proposed manage to create feasible and efficient high school timetables, thus fulfilling adequately the timetabling needs of the respective high schools. Computational results demonstrate that both algorithms manage to reach efficient solutions, most of the times better than existing approaches applied to the same school timetabling input instances using the same evaluation criteria. View Full-Text
Keywords: school timetabling; particle swarm optimization; artificial fish swarm school timetabling; particle swarm optimization; artificial fish swarm
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Katsaragakis, I.V.; Tassopoulos, I.X.; Beligiannis, G.N. A Comparative Study of Modern Heuristics on the School Timetabling Problem. Algorithms 2015, 8, 723-742.

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