Adaptive temperature schedule determined by genetic algorithm for parallel simulated annealing

Simulated annealing (SA) is an effective general heuristic method for solving many combinatorial optimization problems. This paper deals with two problems in SA. One is the long computational time of the numerical annealings, and the solution to it is the parallel processing of SA. The other one is the determination of the appropriate temperature schedule in SA, and the solution to it is the introduction of an adaptive mechanism for changing the temperature. The multiple SA processes are performed in multiple processors, and the temperatures in the SA processes are determined by a genetic algorithms. The proposed method is applied to solve many TSPs (Traveling Salesman Problems) and JSPs (Jobshop Scheduling Problems), and it is found that the method is very useful and effective.