Simulated Annealing Algorithm and Its Applications

This paper introduces and analyses a kind of new heuristic optimization method——simulated annealing algorithm. It is a general random search algorithm based on Monte-Carlo iterative improvement method. The paper gives a sufficient condition for the convergence of simulated annealing algorithm; analyses the main parameters of the algorithm; and discusses its various applications, such as computer design, image processing, and neural net computation, etc.