Abstract
Examination timetable scheduling is a serious challenge in every University system with concerns on assigning examinations to venues over a period of time. Major challenges facing examination scheduling includes: having student’s population to be much more than the available resources, availability of examination venues for the examinations within limited time periods and satisfying all constraints is becoming increasingly difficult. An enhanced particle swarm optimization (PSO) was employed for unraveling the examination timetable scheduling problems at the Federal University of Agriculture, Abeokuta, Nigeria. A combined approach using PSO with local search mechanism was used to enhance the effectiveness of the algorithm against the manual timetabling method. PSO algorithm and local search technique was implemented using Java to develop an examination timetabling system, however, PSO algorithm could not provide a perfectly feasible solution for the University examination timetable but approaches a near-optimal solution with the integration of local search technique.
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We acknowledge the support and sponsorship provided by Covenant University through the Centre for Research, Innovation and Discovery (CUCRID).
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Abayomi-Alli, O., Abayomi-Alli, A., Misra, S., Damasevicius, R., Maskeliunas, R. (2019). Automatic Examination Timetable Scheduling Using Particle Swarm Optimization and Local Search Algorithm. In: Shukla, R.K., Agrawal, J., Sharma, S., Singh Tomer, G. (eds) Data, Engineering and Applications. Springer, Singapore. https://doi.org/10.1007/978-981-13-6347-4_11
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DOI: https://doi.org/10.1007/978-981-13-6347-4_11
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