Title :
Optimize Timetabling Problem Using Improved Genetic Algorithm
Author :
Yun, Wang Xiang ; Kun, Wang Feng ; Wang Xiang Yun
Author_Institution :
Coll. of Manage., HangZhou DianZi Univ., Hangzhou
Abstract :
The arrange timetable algorithms in common need to further improve. Aiming at the problem, classes divide into groups and elitist strategy with dissimilarity chromosome methods based on genetic algorithms (GA) was proposed. Compared with standard genetic algorithms by simulation, its efficiency was demonstrated. The experimental results show that it illustrates a good prospect of application and extension.
Keywords :
education; genetic algorithms; graph theory; scheduling; bipartite graph; dissimilarity chromosome methods; education; genetic algorithm; timetabling problem optimisation; Biological cells; Bipartite graph; Computer science; Costs; Educational institutions; Educational programs; Genetic algorithms; Paper technology; Programming profession; Technology management; adaptive; bipartite graph; genetic algorithm; timetable problem;
Conference_Titel :
Knowledge Acquisition and Modeling Workshop, 2008. KAM Workshop 2008. IEEE International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3530-2
Electronic_ISBN :
978-1-4244-3531-9
DOI :
10.1109/KAMW.2008.4810475
