000			02157nam a2200241 4500
001			UPMIN-00000010146
003			UPMIN
005			20230206172931.0
008			230206b |||||||| |||| 00| 0 eng d
040			_aDLC _cUPMin _dupmin
041			_aeng
090			_aLG993.5 2004 _bA64 O39
100	1		_aOguis, GB Winston R. _92139
245	0	0	_aA university course timetabling using genetic algorithm / _cGB Winston R. Oguis
260			_c2004
300			_a46 leaves
502			_aThesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2004
520	3		_aTimetabling 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.
658			_aUndergraduate Thesis _cAMAT200, _2BSAM
905			_aFi
905			_aUP
942			_2lcc _cTHESIS
999			_c449 _d449