模拟退火fortran程序,可以根据优化函数设置参数-C　 Simulated annealing is a global optimization method that distinguishes

C　 between different local optima. Starting from an initial point, the

C　 algorithm takes a step and the function is evaluated. When minimizing a

C　 function, any downhill step is accepted and the process repeats from this

C　 new point. An uphill step may be accepted. Thus, it can escape from local

C　 optima. This uphill decision is made by the Metropolis criteria. As the

C　 optimization process proceeds, the length of the steps decline and the

C　 algorithm closes in on the global optimum. Since the algorithm makes very

C　 few assumptions regarding the function to be optimized, it is quite

C　 robust with respect to non-quadratic surfaces. The degree of robustness

C　 can be adjusted by the user. In fact, simulated annealing can be used as

C　 a local optimizer for difficult functions.