Simulated Annealing (SA) is a metaheuristic, inspired by annealing process. SA starts with an initial solution at higher temperature, where the changes are accepted with higher probability. So the exploration capability of the algorithm is high and the search space can be explored widely. As the algorithm continues to run, the temperature decreases gradually, like the annealing process, and the acceptance probability of non-successful moves, decrease. Simulated Annealing is proposed by Kirkpatrick et al., in 1993. You can get more information about SA, in the realted article of Wikipedia, here.
In this post, we are going to share with you, the open-source MATLAB implementation of Simulated Algorithm, which is used to solve the Traveling Salesman Problem (TSP). In addition to standard version of SA, implementation of a Population-based Simulated Annealing is also provided within the download package. The algorithms are implemented in a structured manner and if you are familiar with MATLAB programming language, you will find it easy, to use the codes in your research projects.
The download link of this project follows.
Implementation of Simulated Annealing (SA) in MATLABDownload