scholarly journals A matheuristic for exam timetabling

2016 ◽  
Vol 49 (12) ◽  
pp. 1289-1294 ◽  
Author(s):  
Taha Arbaoui ◽  
Jean-Paul Boufflet ◽  
Aziz Moukrim
Keyword(s):  
Exam Timetabling

scholarly journals Search with evolutionary ruin and stochastic rebuild: A theoretic framework and a case study on exam timetabling

2015 ◽  
Vol 242 (3) ◽  
pp. 798-806 ◽  
Author(s):  
Jingpeng Li ◽  
Ruibin Bai ◽  
Yindong Shen ◽  
Rong Qu
Keyword(s):  
Exam Timetabling

scholarly journals Genetic Algorithm for Exam Timetabling Problem - A Specific Case for Japanese University Final Presentation Timetabling

2020 ◽  
Author(s):  
Jiawei LI ◽  
Tad Gonsalves
Keyword(s):  
Genetic Algorithm ◽  
Real Data ◽  
Initial Population ◽  
Exam Timetabling ◽  
Timetabling Problem ◽  
Training Approach ◽  
Chromosome Representation ◽  
Genetic Algorithm Approach ◽  
Hard And Soft Constraints ◽  
Microsoft Office

This paper presents a Genetic Algorithm approach to solve a specific examination timetabling problem which is common in Japanese Universities. The model is programmed in Excel VBA programming language, which can be run on the Microsoft Office Excel worksheets directly. The model uses direct chromosome representation. To satisfy hard and soft constraints, constraint-based initialization operation, constraint-based crossover operation and penalty points system are implemented. To further improve the result quality of the algorithm, this paper designed an improvement called initial population pre-training. The proposed model was tested by the real data from Sophia University, Tokyo, Japan. The model shows acceptable results, and the comparison of results proves that the initial population pre-training approach can improve the result quality.

Exam timetabling with allowable conflicts within a time window

2019 ◽  
Vol 127 ◽  
pp. 263-273 ◽  
Author(s):  
Omar Abou Kasm ◽  
Baraa Mohandes ◽  
Ali Diabat ◽  
Sameh El Khatib
Keyword(s):  
Time Window ◽  
Exam Timetabling

A mixed-integer mathematical modeling approach to exam timetabling

2007 ◽  
Vol 7 (1) ◽  
pp. 19-46 ◽  
Author(s):  
Salem M. Al-Yakoob ◽  
Hanif D. Sherali ◽  
Mona Al-Jazzaf
Keyword(s):  
Mathematical Modeling ◽  
Mixed Integer ◽  
Exam Timetabling ◽  
Modeling Approach

scholarly journals A study on university course and exam timetabling problems and methods: an optimization survey

2018 ◽  
Vol 7 (2.14) ◽  
pp. 191
Author(s):  
Ahmad Firdaus Khair ◽  
Mokhairi Makhtar ◽  
Munirah Mazlan ◽  
Mohamad Afendee Mohamed ◽  
Mohd Nordin Abdul Rahman
Keyword(s):  
Reliable Method ◽  
Exam Timetabling ◽  
Timetabling Problem ◽  
University Timetabling ◽  
University Course

The objective of this paper was to retrieve the overview approaches that have been proposed and classification constraints related to previ-ous papers of timetabling problems. Optimisation and scheduling are essential problems in every type of timetabling that can be considered as a non-deterministic polynomial. The objective of this paper to investigate the course and exam timetabling problem by presented classifi-cation table of set of constraints and describes the most reliable method that has been used to solve university timetabling problem. The re-sult of study concerned the two most successfully method that widely used for optimising course and exam timetable. The contribution of this study also help to provide knowledge and idea for further surveys. 

Parallel Scatter Search Algorithms for Exam Timetabling

2011 ◽  
Vol 2 (3) ◽  
pp. 27-44 ◽  
Author(s):  
Nashat Mansour ◽  
Ghia Sleiman-Haidar
Keyword(s):  
Heuristic Algorithms ◽  
Scatter Search ◽  
Search Space ◽  
Population Based ◽  
Search Algorithms ◽  
Sequential Algorithm ◽  
Solution Quality ◽  
Reasonable Time ◽  
Exam Timetabling ◽  
Communication Techniques

University exam timetabling refers to scheduling exams into predefined days, time periods and rooms, given a set of constraints. Exam timetabling is a computationally intractable optimization problem, which requires heuristic techniques for producing adequate solutions within reasonable execution time. For large numbers of exams and students, sequential algorithms are likely to be time consuming. This paper presents parallel scatter search meta-heuristic algorithms for producing good sub-optimal exam timetables in a reasonable time. Scatter search is a population-based approach that generates solutions over a number of iterations and aims to combine diversification and search intensification. The authors propose parallel scatter search algorithms that are based on distributing the population of candidate solutions over a number of processors in a PC cluster environment. The main components of scatter search are computed in parallel and efficient communication techniques are employed. Empirical results show that the proposed parallel scatter search algorithms yield good speed-up. Also, they show that parallel scatter search algorithms improve solution quality because they explore larger parts of the search space within reasonable time, in contrast with the sequential algorithm.

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