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In this chapter we will examine another technique that allows you to train neural networks. In Chapter 8 you were introduced to using genetic algorithms to train a neural network. This chapter will show you how you can use another popular algorithm, which is named simulated annealing. Simulated annealing has become a popular method of neural network training. As you will see in this chapter, it can be applied to other uses as well.

This chapter will show you how simulated annealing can be used to solve problems. The example program that is presented in this chapter solves the traveling salesman problem, just like the genetic algorithm in Chapter 8 did. This time, however, simulated annealing will be used in place of the genetic algorithm. This will allow you to see some of the advantages that simulated annealing offers over a genetic algorithm.

This chapter will begin by giving you a general background of the simulated annealing process. Next we will construct a class that is capable of using simulated annealing to solve the traveling salesman problem. Both Chapter 8 and 9 are leading up to Chapter 10, which is where you will see how both simulated annealing and genetic algorithms can be used to train a neural network. We will begin this chapter by introducing the simulated annealing algorithm.