Two stages best first search algorithm using hard and soft constraints heuristic for course timetabling

Course Timetabling is to combine the components of teachers, students, subjects, and time. The schedule consists of days on the horizontal axis and time of the clock on the vertical axis. The best first search algorithm is an algorithm to find a solution from existing nodes. Nodes can be various types of problems. In this case, the node is a two-dimensional schedule. In course timetabling there are several constraints or called heuristic functions that must be calculated. The Heuristic function consists of two parts. The first part is a constraint that must be fulfilled (Hard Constraint). There is a schedule of conflicts of the demands of the teacher cannot teach at a certain time. The second part is a constraint which is an optimization to make the search results better in heuristic value (Soft Constraint). Student schedules and teachers are worked out sequentially so students do not wait too long. Best First Search algorithm is designed in two stages. The first step is to find the first heuristic value that must be fulfilled. The second step is to find the second heuristic value. The quality of the solution obtained is between 40% -75%. The significance of this research is that dividing the Best First Search algorithm into two stages yields advantages in terms of meeting hard constraints and the time needed to process the algorithm better. © 2020 Lavoisier. All rights reserved.