Simulated Annealing for the Traveling Salesman Problem
This program was written to solve the Traveling Salesman Problem using simulated annealing, a basic form of artificial intelligence. Given a set of points on a map, the problem asks us to find the shortest possible route that can be taken to visit every single point. Simulated annealing attempts to solve this problem by introducing a temperature variable that aids us in finding the maxima for any given function. The screenshots below display various states of a set of points given changes in this temperature variable and a cooling factor that controls the rate at which the simulated annealing occurs. The first image represents a very low cooling factor which makes the path non-optimal. The second image shows Simulated Annealing at work, reducing the total distance of the path by a significant margin. The program was developed in WPF using C# & XML.
About Me
Based in the United States, I work on Software Development in various programming languages. I have experience in C, C++, C#, Java, Python, and web-related languages and markups including HTML5, JavaScript, PHP, ASP.NET, and various JavaScript libraries. I also have familiarity with a wide breadth of API's, including those for Android.
