DOI : https://doi.org/10.18517/ijaseit.10.2.10231

Heuristic Algorithm for Multi-Location Lecture Timetabling

San Nah Sze (1), Huiggy Kuan (2), Kang Leng Chiew (3), Wei King Tiong (4), Chin Siong Heng (5)
(1) Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300, Sarawak, Malaysia
(2) Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300, Sarawak, Malaysia
(3) Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300, Sarawak, Malaysia
(4) Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300, Sarawak, Malaysia
(5) Faculty of Cognitive Sciences and Human Development, Universiti Malaysia Sarawak, 94300, Sarawak, Malaysia
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How to cite (IJASEIT) :
Sze, San Nah, et al. “Heuristic Algorithm for Multi-Location Lecture Timetabling”. International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 2, Mar. 2020, pp. 455-60, doi:10.18517/ijaseit.10.2.10231.
Citation Format :
This paper studies a real faculty timetabling problem with multi-location consideration. Faculty of Cognitive Sciences and Human Development, UNIMAS offers a master's program by coursework to postgraduate students. The construction of timetables for all the courses offered is a tedious process due to constraints such as team-teaching allocation, unavailability dates of lecturers, and multi-location considerations. Therefore, a manually designed timetable is not as practical as it is time consuming when operational constraints must be fulfilled. In this paper, a two-stage heuristic algorithm is proposed to solve this postgraduate coursework timetable problem. This is because the heuristic algorithm is easy to apply and able to generate a feasible solution in a short time. The proposed two-stage heuristic algorithm consists of Lecturer Grouping Stage and Group Allocation Stage. In Stage I, the lecturers are assigned into four lecturer groups with the condition of no identical lecturers in each of the groups. Then, in Stage II, these groups are allocated into a set of academic weeks throughout the semester. The timeslot for each course can be allocated, and the team-teaching slot for the lecturers can be assigned in this stage. The result from the two-stage heuristic algorithm shows remarkable improvement over the real timetables solution by analyzing the distribution of lecture sessions of the courses.

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