Computerised Heuristic Algorithm for Multi-location Lecture Timetabling - Kuan, Huiggy (Universiti Malaysia Sarawak (UNIMAS), 2020)
This research focuses on multi-location coursework timetabling problem for Master of Science in Human Resource Development (MSc HRD) at the Faculty of Cognitive Sciences and Human Development (FCSHD), Universiti Malaysia Sarawak (UNIMAS). The MSc HRD degree is designed especially for working professionals to seek advanced knowledge, skills and confidence in the areas of human resource development and management. The courses are conducted during weekends. Apart from the main campus at Kota Samarahan it is also being offered at other learning centres in Malaysia, in order to fulfil the high market demand to obtain a master degree. Due to this, the lecturers are assigned to different teaching locations. This situation has made the timetabling of lectures very challenging. Moreover, the process of current manual timetabling practice to produce a clash-free timetable is time-consuming. Besides that, the current timetabling practice needs to fulfil constraints such as where lecturer’s unavailable dates, different types of teaching slot, team-teaching among lecturers, the lecturer can only conduct one course or at one location at one time, total teaching hours for a course and even distribution of lecture sessions and lecturer duty. The objective of this study is to design a heuristic model for multi-location timetabling problem. A two-stage heuristic algorithm is proposed to solve the multi-location timetabling problem on MSc HRD coursework programme. The proposed two-stage heuristic algorithm consists of Lecturer Grouping Stage which allocates the lecturers into different team-teaching groups. After that, the algorithm proceeds to Group Allocation Stage in a round robin optimisation. The lecturer’s unavailability is considered in Stage II as well. Real data from two semesters were collected from FCSHD to test the feasibility of the proposed solution. The simulator generates clash-free timetable in less than a minute, while fulfilling the unavailability dates of lecturers and different types of teaching slot. On average, more than 80% of the timetabled days fall within the acceptable range of the week’s break between lecture sessions. A set of sensitivity analysis has also been conducted under different scenarios, such as the unavailability dates of lecturers, teaching slot type for locations and team-teaching basis. The results show that the proposed solution is effective and robust in solving MSc HRD coursework programme multi-location timetabling problem.