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Title: University Course Timetabling using Bayesian based Optimization Algorithm
Authors: Siame, Alinaswe
Kunda, Douglas
Keywords: Mulungushi University, Kabwe, Zambia
Issue Date: 2017
Publisher: JES
Citation: IEEE Style
Abstract: The timetabling problem has traditionally been treated as a mathematical optimization, heuristic, or human-machine interactive problem. The timetabling problem comprise of hard and soft constraints. Hard constraints must be satisfied in order to generate feasible solutions. Soft constraints are sometimes referred as preferences that can be contravened if necessary. In this research, we present is as both a mathematical and a human-machine problem that requires acceptable and controlled human input, then the algorithm gives options available without conflicting the hard constraints. In short, this research allows the human agents to address the soft-constraints as the algorithm works on the hard constraints, as well as the algorithm being able to learn the soft constraints over time. Simulation research was used to investigate the time tabling problem. Our proposed model employs the use a naïve Bayesian Algorithm, to learn preferred days and timings by lecturers and use them to resolve the soft constraints. Keywords—Algorithms
Description: Research
Appears in Collections:Research Papers and Journal Articles

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