Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2004

Timetabling is an assignment-type problem that deals with properly listing university programs. It is classified into two types: examination timetabling and course timetabling. Whichever timetabling it is, this involves two types of constraints: s Oft and hard. Hard constraints are constraints that should always be satisfied by a timetable while soft constraints are only optional but desirable whenever satisfied. This study employed genetic algorithm, a meta-heuristics method that simulates the biological process of cell division and replication as observed in cellular mitosis. This algorithm involves several sub-algorithms such as data recombination, mutation, evaluation, and the generation of a new population of timetables. These algorithms were the applied on the data obtained from the College of Science and Mathematics (CSM) in the University of the Philippines in Mindanao as a timetabling problem. A total of thirty (30) timetables was obtained from the application of the algorithm. The raw data that was obtained from the University was translated into vector codes to facilitate checking of conflicts and mapped into a matrix. Following the algorithm created, manual manipulation as then employed to obtain the succeeding timetables. An evaluation function was created based on the set of hard and soft constraints and was maximized. Thus, a genetic algorithm CSM was formulated and implemented for producing feasible populations of timetables.