DocumentCode :
3276057
Title :
Solving department´s course-scheduling Problem using differential evolution
Author :
Salman, Ayed A. ; Hamdan, Suha A.
Author_Institution :
Coll. of Eng., Comput. Eng. Dept., Kuwait Univ., Safat, Kuwait
fYear :
2009
fDate :
14-15 Dec. 2009
Firstpage :
1
Lastpage :
8
Abstract :
Department´s course scheduling problem involves assigning courses, timeslots, and rooms to faculty members. However, due to the large number of constraints that must be handled, searching for an optimal solution for course scheduling problem is considered to be a complex and a time-consuming task. Methods used nowadays in many educational institutes depend on a manual process that is performed by one or more experienced personals in course scheduling. These methods are most likely to be ??greedy?? in their approach so as they resolve a portion, not all of the problem´s constraints. Such methods take in general from several hours to weeks of negotiation and bargaining to resolve one or more constraints. This paper presents the first attempt (to the authors´ best knowledge) in using DE algorithm to solve the course scheduling problem. A case study is taken from the Computer Engineering (CPE) department at the college of Engineering and Petroleum in Kuwait University (KU). A wide set of practical constraints is taken into consideration. Moreover, the desired solution is compared to ad-hoc manual optimization, semi-randomized optimization and to hybrid algorithm, to show that not only the execution time is reduced dramatically but also that the proposed method can improve the quality of solutions.
Keywords :
educational administrative data processing; educational courses; educational institutions; evolutionary computation; optimisation; scheduling; College of Engineering and Petroleum; DE algorithm; Kuwait University; ad-hoc manual optimization; computer engineering department; course scheduling problem; department course-scheduling problem; differential evolution; educational institutes; faculty members; hybrid algorithm; semi-randomized optimization; Educational institutions; Evolutionary computation; Genetic algorithms; Job shop scheduling; Linear programming; Optimization methods; Petroleum; Processor scheduling; Scheduling algorithm; Testing; Course-scheduling; Differential Evolution; Evolutionary Algorithms; Timetabling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Methods and Models in Computer Science, 2009. ICM2CS 2009. Proceeding of International Conference on
Conference_Location :
Delhi
Print_ISBN :
978-1-4244-5051-0
Type :
conf
DOI :
10.1109/ICM2CS.2009.5397988
Filename :
5397988
Link To Document :
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