A Mutation Based Genetic Algorithm for Room and Proctor Assignment in Examination Scheduling

Hosny, Manar and Al-olayan, Muhrah (2014) A Mutation Based Genetic Algorithm for Room and Proctor Assignment in Examination Scheduling. In: Science and information, 2014, London, UK.

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Official URL: https://www.researchgate.net/publication/266672561...


— Examination scheduling is a very important task that has to be done in all academic institutions periodically. Formulating exam schedules manually requires immense time and effort, due to the presence of a large number of conflicting constraints that must be satisfied. In this study, we tackle the examination scheduling problem that is specific to the female section in our college, and particularly to the Masters program. Due to cultural restrictions, different room types may be needed to schedule exams, if the instructor is of a different gender than the students. In addition, proctors should be assigned to supervise these exams. We propose a Genetic Algorithm (GA) approach to solve the problem. Our approach follows the classical GA framework but without the crossover operator. We consider mutation as the main genetic operator during the evolutionary process, in order to avoid disruption of constraints and maintain the feasibility of solutions as much as possible. For our examination scheduling problem, two optimization phases have been developed. In the first phase, we find the best room assignment, in terms of room type and the appropriate number of seats for each exam. While in the second phase, the exams will be assigned to proctors for supervision. Each of these phases has a different set of hard constraints that have to be satisfied in the solution. In addition, there are also soft constraints, which should be optimized to improve the quality of the solution. The experimental results indicate the efficiency of the algorithm in handling the constraints that are specific to this examination scheduling problem.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computer Sciences
Divisions: Female College of Sciences and Arts - Khamis Mushyait > Computer Sciences
Depositing User: Mohrah Alalyan
Date Deposited: 20 Aug 2017 10:55
Last Modified: 20 Aug 2017 10:55
URI: http://eprints.kku.edu.sa/id/eprint/994

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