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| Author: | Carrasco, M.P. Pato, M.V. |
| Title: | A comparison of discrete and continuous neural network approaches to solve the class/teacher timetabling problem |
| Journal: | European Journal of Operational Research
2004 : FEB, VOL. 153:1, p. 65-79 |
| Index terms: | Timetabling Scheduling Neural networks Educational institutions |
| Language: | eng |
| Abstract: | This study explores the application of neural network-based heuristics to the class/teacher timetabling problem (CTTP). In this paper the authors consider the scheduling of a set of lessons (class/teacher assignments) subject to hard and soft constraints, and can be modelled in the context of combinatorial optimization. The authors present an experimental comparison of two neural network-based heuristics to tackle the problem. Experimental results on both real-life and randomly-generated instances show the advantages of these ingredients. |
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