General Simulated Annealing

Simulated annealing is a new kind of random search methods developed in recent years.it canalso be considered as an extension to the classical hill-climbing method in AI——probabilistichill-cimbing.One of its most important features is its global convergence.The convergence ofsimulated annealing algorithm is determined by state generating probability,state acceptingprobability,and temperature decreasing rate.This paper gives a generalized simulated annealingalgorithm with dynamic generating and accepting probabilities.The paper also shows that thegenerating and accepting probabilities can adopt many different kinds of distributions while the globalconvergence is guaranteed.