Abstract
Mathematical optimization or mathematical programming is the choice of the best elements from a set of alternatives, according to certain criteria. Extremely complex problems that have become very popular with the development of computer science can be solved by using Mathematical optimization. If it is not possible to determine the exact solution of the problem using traditional methods, we can approach to problem solving by using heuristic methods. Thereby we can determine an approximate solution. One type of the heuristics are metaheuristics. The metaheuristics are very useful approach to the optimization problems, because finding a large set of possible solutions can lead to a good solution with less computing 'effort ' than algorithms, iterative methods and simple heuristics. Simulated Annealing is a type of metaheuristics inspired by the process of the metals annealing that involves heating and controlled cooling of metals to modify the physical properties due to changes occurring in the internal structure of materials. Simulated annealing is a suitable algorithm for solving NP - hard problems such as the Traveling Salesman Problem. This paper presents the pseudocode for solving the Traveling Salesman Problem using the simulated annealing algorithm.
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