A systematic procedure for setting parameters in simulated annealing algorithms

Values of parameters used in simulated annealing (SA) algorithms must be carefully selected since parameter values may have a significant influence on the performance of the algorithm. However, it is not easy to find good parameter values because values of a wide range have to be considered for each parameter and some parameters may be correlated with each other. In this paper, we suggest a procedure which gives good parameter values quickly without much human intervention by using the simplex method for nonlinear programming. To show the performance of the procedure, computational tests are done on a graph partitioning problem, a permutation flowshop scheduling problem and a short-term production scheduling problem. We select values for parameters needed in SA algorithms for the problems using the suggested procedure. The SA algorithms designed with this procedure are compared with existing SA algorithms in which parameter values were selected after extensive experiments.