TY - GEN
T1 - An improved artificial bee colony for Course Timetabling
AU - La'aro Bolaji, Asaju
AU - Tajudin Khader, Ahamad
AU - Azmi Al-Betar, Mohammed
AU - Awadallah, Mohammed A.
PY - 2011
Y1 - 2011
N2 - The Artificial Bee Colony Algorithm (ABC) is an emerging nature-inspired, metaheuristic optimisation algorithm. In this paper, an improved ABC algorithm is proposed for tackling Curriculum-Based Course Timetabling Problem (CBCTT). The ABC as a population-based algorithm, the initial population is generated using Saturation Degree (SD) followed by Backtracking Algorithm (BA) to ensure that all the solutions in the population are feasible. The improvement loop in ABC used neighbourhood structures severally within the employed and onlooker bees operators in order to navigate the CB-CTT search space tightly. The performance of ABC is tested using dataset prepared by second international timetabling competition (ITC-2007), the ABC is able to achieved good quality results, yet these are not comparable with the best results obtained by other methods. Future work can be directed further improve the ABC operators to achieve a better results.
AB - The Artificial Bee Colony Algorithm (ABC) is an emerging nature-inspired, metaheuristic optimisation algorithm. In this paper, an improved ABC algorithm is proposed for tackling Curriculum-Based Course Timetabling Problem (CBCTT). The ABC as a population-based algorithm, the initial population is generated using Saturation Degree (SD) followed by Backtracking Algorithm (BA) to ensure that all the solutions in the population are feasible. The improvement loop in ABC used neighbourhood structures severally within the employed and onlooker bees operators in order to navigate the CB-CTT search space tightly. The performance of ABC is tested using dataset prepared by second international timetabling competition (ITC-2007), the ABC is able to achieved good quality results, yet these are not comparable with the best results obtained by other methods. Future work can be directed further improve the ABC operators to achieve a better results.
KW - Artificial Bee Colony Algorithm
KW - Curriculum Based Course Timetabling
KW - Nature Inspired Algorithm
KW - Neighbourhood structure
UR - https://www.scopus.com/pages/publications/80155165652
U2 - 10.1109/BIC-TA.2011.74
DO - 10.1109/BIC-TA.2011.74
M3 - Conference contribution
AN - SCOPUS:80155165652
SN - 9780769545141
T3 - Proceedings - 2011 6th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2011
SP - 9
EP - 14
BT - Proceedings - 2011 6th International Conference on Bio-Inspired Computing
T2 - 6th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2011
Y2 - 27 September 2011 through 29 September 2011
ER -