Application of Genetic Algorithm and Simulated Annealing Algorithm for Course Scheduling Problem

DOI

10.2991/masta-19.2019.69How to use a DOI?

Keywords

Timetabling problem, Genetic algorithm, Simulated annealing algorithm

Abstract

In this paper, we propose a special course scheduling problem with class combination. By dismantling the restrictions of given classes, students with similar foundations are reorganized into new classes. It helps to improve the efficiency of the class and the acceptance of students. However, it is difficult to arrange new classes and time artificially, considering class capacity and the conflict with other courses. And as the number of class increases, the calculation time shows an exponential growth, which is an NP-hard problem. In order to solve this problem, we use genetic algorithm and simulated annealing algorithm to get the optimal solution.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Deng-yu-hui Li
AU  - Jia-ji Shen
AU  - Hui-zhu Dong
AU  - Yi-ran Su
AU  - Zhi-gang Zhang
PY  - 2019/07
DA  - 2019/07
TI  - Application of Genetic Algorithm and Simulated Annealing Algorithm for Course Scheduling Problem
BT  - Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)
PB  - Atlantis Press
SP  - 408
EP  - 413
SN  - 1951-6851
UR  - https://doi.org/10.2991/masta-19.2019.69
DO  - 10.2991/masta-19.2019.69
ID  - Li2019/07
ER  -