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Simulated annealing (SA) is an effective general heuristic method for solving many optimization problems. This paper deals with the 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 neighborhood range in SA, and the solution to it is the introduction of an adaptive mechanism for changing the neighborhood range. The multiple SA processes are performed in multiple processors, and the neighborhood range in the SA processes are determined by a genetic algorithms. The proposed method is applied to solve many continuous optimization problems, and it is found that the method is very useful and effective.