Courses timetabling problem by minimizing the number of less preferable time slots

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Abstract

In an organization with large number of resources, timetabling is one of the most important factors of management strategy and the one that is most prone to errors or issues. Timetabling the perfect organization plan is quite a task, thus the aid of operations research or management strategy approaches is obligation. Timetabling in educational institutions can roughly be categorized into school timetabling, course timetabling, and examination timetabling, which differ from each other by their entities involved such as the type of events, the kind of institution, and the type and the relative influence of constraints. Education timetabling problem is generally a kind of complex combinatorial problem consisting of NP-complete sub-problems. It is required that the requested timetable fulfills a set of hard and soft constraints of various types. In this paper we consider a courses timetabling problem at university whose objective is to minimize the number of less preferable time slots. We mean by less preferable time slots are those devoted in early morning (07.00-07.50 AM) or those in the late afternoon (17.00-17.50 AM) that in fact beyond the working hour, those scheduled during the lunch break (12.00-12.50 AM), those scheduled in Wednesday 10.00-11.50 AM that coincides with Department Meeting, and those in Saturday which should be in fact devoted for day-off. In some cases, timetable with a number of activities scheduled in abovementioned time slots are commonly encountered. The courses timetabling for the Educational Program of General Competence (PPKU) students at odd semester at Bogor Agricultural University (IPB) has been modelled in the framework of the integer linear programming. We solved the optimization problem heuristically by categorizing all the groups into seven clusters.

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APA

Oktavia, M., Aman, A., & Bakhtiar, T. (2017). Courses timetabling problem by minimizing the number of less preferable time slots. In IOP Conference Series: Materials Science and Engineering (Vol. 166). Institute of Physics Publishing. https://doi.org/10.1088/1757-899X/166/1/012025

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