An Evolutionary Approach to the School Timetabling Problem
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چکیده
We present a general heuristic technique that solves a timetabling problem, such as school timetabling. It is based on a Hopfield-type neural network, whose complexity was significantly reduced by incorporating a genetic algorithm into a very first stage of the timetabling process. The goal of the GA was to initialize the network so that the number of neurons and their connections decreased, and as a consequence the computation speeded up. By using this technique, we were able to produce school timetables subject to both hard and soft constraints in a reasonable polynomial time. The technique proved to be an efficient method for solving a NP-complete combinatorial optimization problem.
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