Improved degraded ceiling algorithm for the expected optimal value

Degraded ceiling algorithm is an intelligent heuristic search algorithm. The expected optimal value of the traditional degraded ceiling algorithm needs to be set. When the expected optimal value of the issue is unknown, the output of hill-climbing algorithm could be used as the expected optimal value. In this paper the result of simulated annealing is used as the initial expected optimal value, meanwhile add outer loop, output of current iteration is taken as the expected optimal value of the next degraded ceiling algorithm. Compare to the traditional way, the improved algorithm is not easy to fall into local optimal solution and the solution quality has been improved, too. Finally, it is applied to solve the traveling salesman problem (TSP). The simulation result has proved the effectiveness of the improved degraded ceiling algorithm.