Electronic Lecture Time-Table Scheduler Using Genetic Algorithm

Soyemi, Jumoke and Akinode, J.L. and Oloruntoba, S.A. (2017) Electronic Lecture Time-Table Scheduler Using Genetic Algorithm. In: 15th IEEE International Conference on Dependable, Autonomic and Secure Computing (IEEE DASC, 2017), 6-10 November, 2017, Orlando, Florida, USA.

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Lecture time-tabling preparation has always been known as a typical scheduling problem that is time consuming, energy sapping and often leading to general apathy and waste of resources. Planning time-table every session or semester is among the most complex and error-prone task carried out in higher institutions of learning. Therefore, the need to adopt an electronic system as opposed to the manual process cannot be over-emphasized. Several other administrative sectors of most institutions have been automated, but lecture time-tabling is still done manually because of its inherent problems. Planning lecture time-table demands enormous attention and effort from any institution because of its constraint satisfaction problem. The Federal Polytechnic Ilaro, the case study in this research operates a Manual time tabling system (MTTS) that is done centrally, which makes it more difficult in getting a flawless lecture scheduling. This study developed an electronic lecture time-table scheduler (ELTS) using Genetic algorithm to provide convenience in fixing classes and reduction in the risk of omission and clashes of courses, halls and lecturers. Questionnaire was also prepared and administered to sample the opinions of staff, students and committee members involved in the manual process. Difference in mean response on the two response variables of ELTS and MTTS was tested using Paired Sample T-test technique. The result from the analysis corroborates the fact that the new ELTS will be the best method in tackling the lapses experienced by the old system.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Unnamed user with email [email protected]
Date Deposited: 01 May 2020 20:17
Last Modified: 01 May 2020 20:17
URI: http://eprints.federalpolyilaro.edu.ng/id/eprint/29

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