scholarly journals Solving examination timetabling problem in UniSZA using ant colony optimization

2018 ◽  
Vol 7 (2.15) ◽  
pp. 132
Author(s):  
Ahmad Firdaus Khair ◽  
Mokhairi Makhtar ◽  
Munirah Mazlan ◽  
Mohamad Afendee Mohamed ◽  
Mohd Nordin Abdul Rahman
Keyword(s):  
Ant Colony ◽  
Educational Institutions ◽  
Ant System ◽  
Examination Timetabling ◽  
Final Exam ◽  
Data Set ◽  
Exam Timetabling ◽  
Timetabling Problem ◽  
Hard Problems ◽  
Occurrence Matrix

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.  

scholarly journals A hybrid Ant Colony Algorithm for the exam timetabling problem

2010 ◽  
Vol Volume 12, 2010 ◽  
Author(s):  
R. Abounacer ◽  
J. Boukachour ◽  
B. Dkhissi ◽  
A. El Hilali Alaoui
Keyword(s):  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Educational Institutions ◽  
Examination Timetabling ◽  
Exam Timetabling ◽  
Timetabling Problem ◽  
Computer Scientists ◽  
International Audience ◽  
Regulation Changes ◽  
With Memory

International audience Due to increased student numbers and regulation changes educational institutions that allow for greater flexibility, operations researchers and computer scientists have renewed their interest in developing effective methods to resolve the examination timetabling problem. Thus, in the intervening decades, important progress was made in the examination timetabling problem with appearance of adaptation of meta-heuristics. This paper presents a hybridization of the Ant Colony Algorithm and a Complete Local search with Memory heuristic, in order to maximize as much as possible; the free time between consecutive exams for each student, while respecting the conflict constraints, a student cannot sit more than one exam in the same timeslot. Vue l’augmentation du nombre d’étudiants dans les établissements scolaires et universitaires, le nombre d’examens à passer par chaque étudiant et les réformes pédagogiques actuelles, les planifications classiques des cours et des examens ne sont plus suffisantes, ce qui a amené les chercheurs opérationnels et les informaticiens à chercher des nouvelles méthodes pour résoudre le problème d’emploi du temps des examens. Notre travail consiste à planifier les examens de telle sorte à maximiser le temps de séparation entre deux examens consécutifs pour chaque étudiant et ceci en utilisant l’algorithme de colonies de fourmis hybridé avec une technique de recherche locale.

scholarly journals An ant colony algorithm for universiti sultan zainal abidin examination timetabling problem

2019 ◽  
Vol 13 (1) ◽  
pp. 191
Author(s):  
Ahmad Firdaus Khair ◽  
Mokhairi Makhtar ◽  
Munirah Mazlan ◽  
Mohamad Afendee Mohamed ◽  
Mohd Nordin Abdul Rahman
Keyword(s):  
Ant Colony Algorithm ◽  
Educational Institution ◽  
Real Life ◽  
Ant Colony ◽  
Ant Colony Optimisation ◽  
Examination Timetabling ◽  
Timetabling Problem ◽  
College And University ◽  
Academic Management ◽  
And Performance

The real-life construction of examination timetabling problem is considered as a common problem that always encountered and experienced in educational institution whether in school, college, and university. This problem is usually experienced by the academic management department where they have trouble to handle complexity for assign examination into a suitable timeslot manually. In this paper, an algorithm approach of ant colony optimisation (ACO) is presented to find an effective solution for dealing with Universiti Sultan Zainal Abidin (UniSZA) examination timetabling problems. A combination of heuristic with ACO algorithm contributes the development solution in order to simplify and optimize the pheromone occurrence of matrix updates which include the constraints problem. The implementation of real dataset instances from academic management is applied to the approach for generating the result of examination timetable. The result and performance that obtained will be used for further use to evaluate the quality and observe the solution whether our examination timetabling system is reliable and efficient than the manual management that can deal the constraints problem.

scholarly journals University course timetabling model using ant colony optimization algorithm approach

2019 ◽  
Vol 13 (1) ◽  
pp. 72 ◽  
Author(s):  
Munirah Mazlan ◽  
Mokhairi Makhtar ◽  
Ahmad Firdaus Khair Ahmad Khairi ◽  
Mohamad Afendee Mohamed
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Problems ◽  
Ant Colony ◽  
Data Set ◽  
Course Timetabling ◽  
Timetabling Problem ◽  
Combinatorial Optimization Problems ◽  
University Course Timetabling ◽  
Course Timetabling Problem ◽  
University Course

<p>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.</p>

Parallel Ant Colony Optimization on the University Course-Faculty Timetabling Problem in MSU-IIT

2012 ◽  
Author(s):  
Earth B. Ugat ◽  
Jennifer Joyce M. Montemayor ◽  
Mark Anthony N. Manlimos ◽  
Dante D. Dinawanao
Keyword(s):  
Ant Colony Optimization ◽  
Ant Colony ◽  
Timetabling Problem ◽  
University Course ◽  
The University

An Enhancement of Feature Selection Algorithm for EDM: A Review

2018 ◽  
Vol 8 (5) ◽  
pp. 29
Author(s):  
Manpreet Kaur ◽  
Chamkaur Singh
Keyword(s):  
Feature Selection ◽  
Educational Data Mining ◽  
Problem Formulation ◽  
Research Area ◽  
Education Quality ◽  
Educational Institutions ◽  
Selection Algorithm ◽  
Positive Role ◽  
Data Set ◽  
Selection Algorithms

Educational Data Mining (EDM) is an emerging research area help the educational institutions to improve the performance of their students. Feature Selection (FS) algorithms remove irrelevant data from the educational dataset and hence increases the performance of classifiers used in EDM techniques. This paper present an analysis of the performance of feature selection algorithms on student data set. .In this papers the different problems that are defined in problem formulation. All these problems are resolved in future. Furthermore the paper is an attempt of playing a positive role in the improvement of education quality, as well as guides new researchers in making academic intervention.

Implementasi Algoritma MAX-MIN Ant System pada Penjadwalan Mata Kuliah

2013 ◽  
Vol 5 (2) ◽  
pp. 48-53
Author(s):  
William Aprilius ◽  
Lorentzo Augustino ◽  
Ong Yeremia M. H.
Keyword(s):  
Ant Colony Optimization ◽  
Ant Colony ◽  
Ant System ◽  
University Course Timetabling ◽  
Alternative Approach ◽  
Ant System Algorithm ◽  
Index Terms ◽  
Course Timetabling Problem ◽  
University Course ◽  
Selection Of

University Course Timetabling Problem is a problem faced by every university, one of which is Universitas Multimedia Nusantara. Timetabling process is done by allocating time and space so that the whole associated class and course can be implemented. In this paper, the problem will be solved by using MAX-MIN Ant System Algorithm. This algorithm is an alternative approach to ant colony optimization. This algorithm uses two tables of pheromones as stigmergy, i.e. timeslot pheromone table and room pheromone table. In addition, the selection of timeslot and room is done by using the standard deviation of the value of pheromones. Testing is carried out by using 105 events, 45 timeslots, and 3 types of categories based on the number of rooms provided, i.e. large, medium, and small. In each category, testing is performed 5 times and for each testing, the data recorded is the unplace and Soft Constraint Penalty. In general, the greater the number of rooms, the smaller the unplace. Index Terms—ant colony optimization, max-min ant system, timetabling

scholarly journals Hybrid Intelligent Water Drops Algorithm for Examination Timetabling Problem

2021 ◽  
Author(s):  
Bashar A. Aldeeb ◽  
Mohammed Azmi Al-Betar ◽  
Norita Md Norwawi ◽  
Khalid A. Alissa ◽  
Mutasem K. Alsmadi ◽  
...  
Keyword(s):  
Examination Timetabling ◽  
Timetabling Problem ◽  
Intelligent Water Drops Algorithm ◽  
Water Drops ◽  
Intelligent Water Drops
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