Research on Time Table Problem Based on Improved Genetic Algorithm Combined Chaos and Simulated Annealing Algorithm
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.
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.
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