The Wise Experiencing Traveling Salesman (WETS): Introduction to a simple evolutionary solution for the problem

In this paper a new idea to solve the traveling salesman problem is introduced. The idea is categorized within meta-heuristic algorithms and is based on a normal wise human-being thinking method. Starting from an arbitrary starting point, three factors are considered to generate a score vector by which the next position is selected. Distance from the non-visited points, successful previous experiments, and a randomly changing factor are the components that make the score vector. The effect of each factor can be adjusted by a weighting parameter. The algorithm is implemented and tested on many small (less than 100 cities) benchmarks. The primary surprising results obtained by this soft computing approach, in comparison to many other recently developed methods, turn a light on its bright perspective to be known as an efficient simple solution to the problem.