Comparison of mutation operators in an evolution strategy-based timetabling for courses in College of Science and Mathematics, University of the Philippines Mindanao /
Ehidio, Jhay O.
Comparison of mutation operators in an evolution strategy-based timetabling for courses in College of Science and Mathematics, University of the Philippines Mindanao / Jhay O. Ihidio - 2010 - 50 leaves, appendix table.
Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2010
University 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
Evolution startegy
Mutation
University course timetabling
Undergraduate Thesis --AMAT200
Fi
Comparison of mutation operators in an evolution strategy-based timetabling for courses in College of Science and Mathematics, University of the Philippines Mindanao / Jhay O. Ihidio - 2010 - 50 leaves, appendix table.
Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2010
University 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
Evolution startegy
Mutation
University course timetabling
Undergraduate Thesis --AMAT200
Fi