Abstract
Many require the use of optimization condition exists in life, and in order to resolve
this situation occurs many optimization algorithm. Simulation is a combination of several
optimization algorithm of simulated annealing algorithm, it is always a hot one
optimization field, received the majority of researchers. As a leader in combination
optimization algorithm, it has compared to other early optimization algorithm more easy to
calculate, the use of flexible advantages of parallel computing, solve the infeasible factor
part of traditional algorithm cannot avoid large-scale problems. Simulated annealing
algorithm derived from the simulated annealing process, in 1953 Metropofis proposed the
advanced ideas, and then by Kirkpatrick et al in 1983 into the optimization in the field,
then the simulated annealing algorithm is one of many in the optimization algorithm. Of
course, this algorithm is not only superior to simple optimization problems in various fields,
which can be used in fields including engineering science in. Simulated annealing
algorithm is very success in every field, but it is in the combinatorial optimization and
occupies a very important position. This paper will make a brief for the simulated
annealing algorithm to make the background, principle and content of the simulated
annealing algorithm. In order to more clearly understand the performance of simulated
annealing, to demonstrate the optimization problem in the performance for the examples in
this article.
In the field of combinatorial optimization problem in NP is always a difficult
problem, especially the well-known traveling salesman problem which has the
characteristics of simple, trouble. Simple refers to the description of the problem is the
most simple, is at several points out the most short path; the trouble is when several points
up to a certain extent is hardly an accurate solution. The simulated annealing algorithm has
a good performance in this problem.
Key words: the simulated annealing algorithm; combinatorial optimization;TSP
