Algorithms of time table problem application and performance evaluation in course scheduling system

This paper analyzes the nature of university curriculum problems (Time table Problem TTP), as well as the strengths and weaknesses of the problem solving, and evaluate some time table problem´s arithmetic performance. The basic algorithm including greedy algorithm, simulated annealing algorithm, genetic algorithm and the improved genetic search algorithm by author. This thesis discover the use of genetic algorithms to solve the problem of arrangement, it has precocious phenomenon and quickly converge the local optimum rather than global optimal solution, so we combine the local search method with partial matching crossover operation, genetic algorithm combined with tabu search to solve the problem. We have carried on the massive experiments to prove it, and analysis and evaluation the performance of the improved algorithm. Experimental results show that genetic search algorithm is a better algorithm for TTP.