000			02564nam a22002773a 4500
001			UPMIN-00004810114
003			UPMIN
005			20230106171343.0
008			230106b |||||||| |||| 00| 0 eng d
040			_aDLC _cUPMin _dupmin
041			_aeng
090		0	_aLG993.5 2010 _bA64 E55
100			_aEhidio, Jhay O. _91272
245			_aComparison of mutation operators in an evolution strategy-based timetabling for courses in College of Science and Mathematics, University of the Philippines Mindanao / _cJhay O. Ihidio
260			_c2010
300			_a50 leaves, appendix table.
502			_aThesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2010
520	3		_aUniversity course timetabling problem is the weekly scheduling of university course lectures, minimizing overlaps of available resources. Evolution strategy, an optimization technique that is based on the principle of survival of the fittest of the evolution concept, is a component method in solving constrained problems. Thus, this study used an evolution strategy-based method in solving the timetabling problem, which is also a constrained problem. Evolution strategy though has not been investigated well and applied extensively in solving course timetabling problems. Thus, this study examined the application of evolution strategy in the course of timetabling problem of the College of Science and Mathematics of the University of the Philippines Mindanao, focusing on the main reproductive operator of evolution strategy that is mutation. The four mutation operators that include 2-exchange, inversion, insertion, and shifting were inserted in the general evolution strategy algorithm, and were compared to know what mutation is the most effective mutation operator. Statistical methods showed that there were no significant differences among the four mutations. Thus, comparison was done by looking at the mutations behavior of convergence to each of their final fitness. Insertion was fund to be the best in fitness improvement, but was also the mutation that has the fastest entrapment at the local optima. With the method tendency of getting trapped at the local optima as what resulted in this study, it is recommended to further study evolution strategy to find better ways in applying it to the course timetabling problem
650	1	7	_aEvolution startegy _91273
650	1	7	_aMutation _91274
650	1	7	_aUniversity course timetabling _91275
658			_aUndergraduate Thesis _cAMAT200
658			_aFi
905			_aUP
942			_2lcc _cTHESIS
999			_c2478 _d2478