Open AccessSolving examination timetabling problem in UniSZA using ant colony optimization
Author(s) -
Ahmad Firdaus Khair,
Mokhairi Makhtar,
Munirah Mazlan,
Mohamad Afendee Mohamed,
Mohd Nordin Abdul Rahman
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.15.11369
Subject(s) - computer science , scheduling (production processes) , mathematical optimization , ant colony , ant colony optimization algorithms , schedule , operations research , key (lock) , set (abstract data type) , job shop scheduling , artificial intelligence , mathematics , computer security , programming language , operating system
At all educational institutions, timetabling is a conventional problem that has always caused numerous difficulties and demands that need to be satisfied. For the examination timetabling problem, those matters can be defined as complexity in scheduling exam events or non-deterministic polynomial hard problems (NP-hard problems). In this study, the latest approach using an ant colony optimisation (ACO) which is the ant system (AS) is presented to find an effective solution for dealing with university exam timetabling problems. This application is believed to be an impressive solution that can be used to eliminate various types of problems for the purpose of optimising the scheduling management system and minimising the number of conflicts. The key of this feature is to simplify and find shorter paths based on index pheromone updating (occurrence matrix). With appropriate algorithm and using efficient techniques, the schedule and assignation allocation can be improved. The approach is applied according to the data set instance that has been gathered. Therefore, performance evaluation and result are used to formulate the proposed approach. This is to determine whether it is reliable and efficient in managing feasible final exam timetables for further use.