scholarly journals A Genetic Algorithm Approach for a Real-World University Examination Timetabling Problem

2010 ◽  
Vol 12 (5) ◽  
pp. 1-4 ◽  
Author(s):  
Oluwasefunmi T. Arogundade ◽  
Adio T. Akinwale ◽  
Omotoyosi M. Aweda
Keyword(s):  
Genetic Algorithm ◽  
Real World ◽  
Examination Timetabling ◽  
Timetabling Problem ◽  
Genetic Algorithm Approach ◽  
University Examination

scholarly journals Heuristic and genetic algorithm approaches to the real-world university examination timetabling problem

2017 ◽  
Vol 7 (1) ◽  
pp. 143-151
Author(s):  
İlker Küçükoğlu ◽  
Alkın Yurtkuran
Keyword(s):  
Genetic Algorithm ◽  
Real World ◽  
Real Life ◽  
Mixed Integer ◽  
Examination Timetabling ◽  
The Real ◽  
Timetabling Problem ◽  
Constructive Heuristic ◽  
Integer Linear Model ◽  
Hard And Soft Constraints

Timetabling is one of the computationally difficult problems in scheduling and aims to find best time slots for a number of tasks which require limited resources. In this paper, we examine different solution approaches for the real-world examination timetabling problem (ETP) for university courses. The problem has unique hard and soft constraints, when compared to previous efforts, i.e. consecutive exams, sharing of rooms, room preferences, room capacity and number of empty slots. The aim of the problem is to achieve a timetable, which minimizes the total number of the examination slots without any conflicts. First, the real-world problem is formally defined and a mixed integer linear model is presented. Then, a constructive heuristic and a genetic algorithm based meta-heuristic are proposed in order to solve the ETP. Proposed approaches are tested on a problem set formed by using a real-life data. Results reveal that, proposed approaches are able to produce superior solutions in a limited time. Keywords: Timetabling, constructive heuristic, genetic algorithm;

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.

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