**6. Conclusions**

This chapter describes the SA with crystallization heuristic and three different applications: cutting and packing, topology optimization and curve interpolation.

*Versatility of Simulated Annealing with Crystallization Heuristic: Its Application… DOI: http://dx.doi.org/10.5772/intechopen.98562*

The cutting and packing problem determines the layout for a set of items to be placed inside a container with fixed dimensions. The cost function is the unused area inside the container. The items can be translated and rotated in the process of determining the layout. This cost function is discrete and the parameters are continuous. As there is no need of any gradient information, it can optimize discrete cost functions.

The topology optimization problem has continuous parameters. The number of parameters is much larger when compared with the cutting and packing problem. Usually, the cost function is one of the two possibilities: volume fraction and compliance. As there are two possibilities for cost function, it is considered the application of the CoAnnealing, which is a multi-objective version of the SA with crystallization heuristic. The last application is the curve interpolation. It has two different types of parameters: continuous and integer. The objective function is composed of two parts: the error between the the given points and the interpolating curve, and the length of the curve. The length of the curve is a regularization to force the curve to be shorter and smoother. The curve interpolation algorithm was used in different applications.

These examples show that the SA with crystallization heuristic is very generic, versatile and easy to implement.
