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- W1545459265 abstract "AbstractIn this paper we present the results of an investigation of the possibilities offered by geneticalgorithms to solve the timetable problem. This problem has been chosen since it is representative ofthe class of multi-constrained, NP-hard, combinatorial optimization problems with real-worldapplication. First we present our model, including the definition of a hierarchical structure for theobjective function and the generalized genetic operators which can be applied to matrices representingtimetables. Then we report about the outcomes of the utilization of the implemented system to thespecific case of the generation of a school timetable. We compare two versions of the geneticalgorithm (GA), with and without local search, both to a handmade timetable and to two otherapproaches based on simulated annealing and tabu search. Our results show that GA with localsearch and tabu search with relaxation both outperform simulated annealing and handmadetimetables.(Introduction)Evolutionary algorithms" @default.
- W1545459265 created "2016-06-24" @default.
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- W1545459265 date "1992-01-01" @default.
- W1545459265 modified "2023-09-23" @default.
- W1545459265 title "A genetic algorithm to solve the timetable problem" @default.
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