Improved Degraded Ceiling Algorithm

Degraded ceiling algorithm is a heuristic optimization algorithm.It is a powerful tool for solving combination optimization problems.The development of degraded ceiling algorithm will lay a foundation for the more practical.The expected optimal value of the traditional degraded ceiling algorithm need to be set.Some concrete problems, such as: the traveling salesman problem which the expected optimal value is unknown.User usually don’t use the degraded ceiling algorithm to solve the problem.This makes the application range of degraded ceiling algorithm is limited. The search path of the algorithm is rate descent, leading to run slower. Therefore, in order to expand the use of degraded ceiling algorithm and speed up the convergence, this paper made the following two aspects of research:(1)Improved degraded ceiling algorithm from the range of application.In some problem which the expected optimal value is unknown, we use the result of simulated annealing as the initial expected optimal value, while add outer loop, take the result of each output as the expected optimal value of the next degraded ceiling algorithm. Repeat this iteration, the expected optimal value and the output result will be better, Finally get a good result. At last, it was applied to solve the traveling salesman problem(TSP) and the results of the improved degraded ceiling algorithm was compared with the Traditional degraded ceiling algorithm, Hill climbing algorithm, Simulated annealing algorithm and Genetic algorithm. Simulation results showed the effectiveness of the improved degraded ceiling algorithm.(2)Improved degraded ceiling algorithm from the search path.The search is rate descent and reduce the convergence speed.We improved the algorithm from constant decline to varying velocity with the principle of "first rough then essence".Such improvement speed up the search speed of the algorithm.Finally use the TSP problem test the effectiveness of the improved algorithm.