Comparison of Performance between Different Selection Strategies on Genetic Algorithm with Course Timetabling Problem
Course timetabling is an NP-hard problem. There are many factors to be considered. A GA is suitable for NP-hard and optimization problems and it can also be applied to various problems. Three main operators of GA are selection, crossover, and mutation. This paper compares performance on a GA when different selection strategies: roulette wheel selection, rank selection, and tournament selection, are applied. A good selection strategy tries to keep good solutions and leave the bad ones out of a population. The experimental result demonstrates that GA with roulette wheel selection works more efficient than the others for producing feasible course timetables.
selection strategies genetic algorithm course timetabling
Wutthipong Chinnasri Nidapan Sureerattanan
Department of Computer Education King Mongkuts University of Technology North Bangkok, Thailand
国际会议
成都
英文
105-108
2010-07-09（万方平台首次上网日期，不代表论文的发表时间）