Open AccessUniversity course timetabling model using ant colony optimization algorithm approach
Author(s) -
Munirah Mazlan,
Mokhairi Makhtar,
Ahmad Firdaus Khair Ahmad Khairi,
Mohamad Afendee Mohamed
Publication year - 2019
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v13.i1.pp72-76
Subject(s) - ant colony optimization algorithms , computer science , flexibility (engineering) , set (abstract data type) , heuristic , metaheuristic , course (navigation) , process (computing) , ant colony , range (aeronautics) , mathematical optimization , operations research , artificial intelligence , algorithm , machine learning , engineering , mathematics , statistics , programming language , aerospace engineering , operating system
Due to the increased number of students and regulations, all educational institutions have renewed their interest to appear in the number of complexity and flexibility since the resources and events are becoming more difficult to be scheduled. Timetabling is the type of problems where the events need to be organized into a number of timeslots to prevent the conflicts in using a given set of resources. Thus in the intervening decades, significant progress has been made in the course timetabling problem monitoring with meta-heuristic adjustment. In this study, ant colony optimization (ACO) algorithm approach has been developed for university course timetabling problem. ACO is believed to be a powerful solution approach for various combinatorial optimization problems. This approach is used according to the data set instances that have been collected. Its performance is presented using the appropriate algorithm. The results are arguably within the best results range from the literature. The performance assessment and results are used to determine whether they are reliable in preparing a qualifying course timetabling process.