Title :
Genetic algorithm and heuristic search for solving timetable problem case study: Universitas Pelita Harapan timetable
Author :
Lukas, Samuel ; Aribowo, Arnold ; Muchri, Milyandreana
Author_Institution :
Inf. Eng., Universitas Pelita Harapan, Tangerang, Indonesia
Abstract :
Scheduling problem is a model of complicated problem. Too many things have to be considered in order to arrange a schedule, such as lecturer availabilities, a great number of classes and courses. To overcome this problem, genetic algorithm combined with heuristic search is proposed in this paper. This proposed method was tested several times, and the results show that despite small population, the best schedule still can be obtained.
Keywords :
educational administrative data processing; genetic algorithms; scheduling; Universitas Pelita Harapan timetable; genetic algorithm; heuristic search; lecturer availabilities; scheduling problem; timetable problem; Biological cells; Computer science; Education; Genetic algorithms; Genetic engineering; Genetic mutations; Informatics; Poles and towers; Processor scheduling; Testing;
Conference_Titel :
Applications of Digital Information and Web Technologies, 2009. ICADIWT '09. Second International Conference on the
Conference_Location :
London
Print_ISBN :
978-1-4244-4456-4
Electronic_ISBN :
978-1-4244-4457-1
DOI :
10.1109/ICADIWT.2009.5273979