TY - GEN
T1 - Solving university examination timetabling problem using intelligent water drops algorithm
AU - Aldeeb, Bashar A.
AU - Norwawi, Norita Md
AU - Al-Betar, Mohammed A.
AU - Jali, Mohd Zalisham Bin
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - This research article aims at proposing Intelligent Water Drops (IWD) algorithm to solve the university examination timetabling problems (UETP). IWD is a recent metaheuristic population-based algorithm belonging to swarm intelligent category which simulate river system. Examination timetabling is a combinatorial optimization problem that is concerned with allocating exams to timeslots efficiently. As an initial study, the IWD Algorithm is tailored to solve uncapacitated examination timetabling problem by using carter 1996 dataset and is able to produce acceptable results, though they were not better than the the results that already reported in the literature. Some examination timetabling heuristic methods such as Saturation degree concepts have been embedded in IWD to ensure the feasibility, while the IWD operators have been trigged to iteratively improve the results.
AB - This research article aims at proposing Intelligent Water Drops (IWD) algorithm to solve the university examination timetabling problems (UETP). IWD is a recent metaheuristic population-based algorithm belonging to swarm intelligent category which simulate river system. Examination timetabling is a combinatorial optimization problem that is concerned with allocating exams to timeslots efficiently. As an initial study, the IWD Algorithm is tailored to solve uncapacitated examination timetabling problem by using carter 1996 dataset and is able to produce acceptable results, though they were not better than the the results that already reported in the literature. Some examination timetabling heuristic methods such as Saturation degree concepts have been embedded in IWD to ensure the feasibility, while the IWD operators have been trigged to iteratively improve the results.
KW - Intelligent water drops algorithm
KW - Scheduling
KW - Uncapacitated examination timetabling problem
UR - https://www.scopus.com/pages/publications/84946147394
U2 - 10.1007/978-3-319-20294-5_17
DO - 10.1007/978-3-319-20294-5_17
M3 - Conference contribution
AN - SCOPUS:84946147394
SN - 9783319202938
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 187
EP - 200
BT - Swarm, Evolutionary, and Memetic Computing - 5th International Conference, SEMCCO 2014, Revised Selected Papers
A2 - Suganthan, Ponnuthurai Nagaratnam
A2 - Panigrahi, Bijaya Ketan
A2 - Das, Swagatam
PB - Springer Verlag
T2 - 5th International Conference on Swarm, Evolutionary and Memetic Computing, SEMCCO 2014
Y2 - 18 December 2014 through 20 December 2014
ER -