Dong Yunfeng
Computer Center, Qilu University of Technology, Jinan, China
ABSTRACT
The scheduling problem is a typical time table problem in educational administration. For such a NP complete problems, when the genetic algorithm solves this problem, it has precociousness phenomenon and quickly converges not to the global optimal solution but to the local optimal solution. Therefore, we use the advantage of simulated annealing algorithm to transform the fitness function and chaotic sequence to control the crossover and mutation genetic operations and then overcome the weakness of genetic algorithm in the Time Table Problem. We do a lot of experiments and evaluate the performance of the improved genetic algorithm. The experiment results show that improved genetic algorithm is a more superior algorithm to apply to the TTP problem.
PDF References Citation
How to cite this article
Dong Yunfeng, 2013. Research on Time Table Problem Based on Improved Genetic Algorithm Combined Chaos and Simulated Annealing Algorithm. Journal of Applied Sciences, 13: 2947-2952.
DOI: 10.3923/jas.2013.2947.2952
URL: https://scialert.net/abstract/?doi=jas.2013.2947.2952
DOI: 10.3923/jas.2013.2947.2952
URL: https://scialert.net/abstract/?doi=jas.2013.2947.2952
REFERENCES
- Dimopoulou, M. and P. Miliotis, 2004. An automated university course timetabling system developed in a distributed environment: A case study. Eur. J. Operat. Res., 153: 136-147.
CrossRef