摘要: Simulated annealing is a new kind of random search methods developed in recent years.it can also be considered as an extension to the classical hill-climbing method in AI——probabilistic hill-cimbing.One of its most important features is its global convergence.The convergence of simulated annealing algorithm is determined by state generating probability,state accepting probability,and temperature decreasing rate.This paper gives a generalized simulated annealing algorithm with dynamic generating and acceptin…