2013Unpublished venueRequires access

Design and implementation of course timetabling system based on genetic algorithm

Hamdy M. Mousa, Ashraf B. El-Sisi

Open publisher page 9 citations

Abstract

University course timetabling is one of the most important and time-consuming problem which takes place frequently in all the educational institutes. This paper proposes design and implementation system to generate timetable based on genetic algorithm using different combinations selection algorithm and mutation types. Two cases small problem and big problem are studied. The results show that two cases tournament selection is giving solutions better than roulette wheel Selection. The worst pair is roulette wheel selection and mutation. Mutation error method helps to reach to the best solution faster. In case of conflicts and no solution, our system generates a report, containing conflict constraints that must be remove or modified.

About this research paper

What this paper is about

University course timetabling is one of the most important and time-consuming problem which takes place frequently in all the educational institutes. This paper proposes design and implementation system to generate timetable based on genetic algorithm using different combinations selection algorithm and mutation types. Two cases small problem and big problem are studied. The results show that two cases tournament selection is giving solutions better than roulette wheel Selection. The worst pair is roulette wheel selection and mutation. Mutation error method helps to reach to the best solution faster. In case of conflicts and no solution, our system generates a report, containing conflict constraints that must be remove or modified.

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OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

University course timetabling is one of the most important and time-consuming problem which takes place frequently in all the educational institutes. This paper proposes design and implementation system to generate timetable based on genetic algorithm using different combinations selection algorithm and mutation types. Two cases small problem and big problem are studied. The results show that two cases tournament selection is giving solutions better than roulette wheel Selection. The worst pair is roulette wheel selection and mutation. Mutation error method helps to reach to the best solution faster. In case of conflicts and no solution, our system generates a report, containing conflict constraints that must be remove or modified.

Key concepts: Tournament selection, Roulette, Fitness proportionate selection, Selection (genetic algorithm), Genetic algorithm, Computer science, Mutation, Tournament

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