DocumentCode :
2215737
Title :
Optimization of university course scheduling problem with a hybrid artificial bee colony algorithm
Author :
Oner, Adalet ; Ozcan, Sel ; Dengi, Derya
Author_Institution :
Dept. of Ind. Eng., Yasar Univ., Izmir, Turkey
fYear :
2011
fDate :
5-8 June 2011
Firstpage :
339
Lastpage :
346
Abstract :
Course scheduling problem (CSP) is concerned with developing a timetable that illustrates a number of courses assigned to the classrooms. In this study, a hybrid algorithm composed of a heuristic graph node coloring (GNC) algorithm and artificial bee colony (ABC) algorithm is proposed to solve CSP. The study is one of the few applications of ABC on discrete optimization problems and to our best knowledge it is the first application on CSP. A basic heuristic algorithm of node coloring problem takes part initially to develop some feasible solutions of CSP. Those feasible solutions correspond to the food sources in ABC algorithm. The ABC is then is used to improve the feasible solutions. The employed and onlooker bees are directed or controlled in a specific manner in order to avoid the conflicts in the course timetable. Proposed solution procedure is tested using real data from a university in Turkey. The experimental results demonstrate that the proposed hybrid algorithm yields efficient solutions.
Keywords :
educational courses; educational institutions; graph colouring; optimisation; ABC algorithm; GNC algorithm; discrete optimization problem; heuristic graph node coloring algorithm; hybrid artificial bee colony algorithm; university course scheduling problem optimization; Arrays; Color; Heuristic algorithms; Job shop scheduling; Optimization; Project management; artificial bee colony algorithm; course scheduling problem; node coloring;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
ISSN :
Pending
Print_ISBN :
978-1-4244-7834-7
Type :
conf
DOI :
10.1109/CEC.2011.5949638
Filename :
5949638
Link To Document :
بازگشت