A Prolog-Based Expert System with Application to University Course Scheduling

University course scheduling is a kind of timetable problem and can be mathematically formulated as an integer linear programming problem. Essentially, a university course scheduling problem is an optimization problem that aims at most efficiently minimizing a cost function according to a set of constraints. The huge searching space for the course scheduling problem means a long time will be needed to find the optimal solution. Therefore, some studies have used soft computing approaches to solve course scheduling problems in order to reduce the searching space. However, in order to use soft computing approaches to solve university course scheduling problems, we may need to design algorithms and conduct numerous experiments to achieve maximum efficiency. Thus, in this study, instead of employing soft computing methods, we propose a SWI-PROLOG-based expert system to solve the course scheduling problem. An experiment was conducted using real-world data from a department at a national university in southern Taiwan. During the experiment, each teacher in the department chose five preferential time slots. The experimental results have shown that about 99% of courses were scheduled in teachers’ five preferential time slots with an acceptable computational time of executing SWI-PROLOG (127 milliseconds on a regular personal computer). This study has thus provided a framework for solving course scheduling problems using an expert system. This would be the main contribution of this study.