Travelling salesman approach for solving visiting route using simulated annealing

This research presents an attempt to solve a student’s problem in the University to travel in seven states in Malaysia, which is Johor, Melaka, Negeri Sembilan, Selangor, Wilayah Persekutuan, Pahang and Terengganu. This traveling system is formulated as a Traveling Salesman Problem (TSP). TSP involves finding an optimal route for visiting areas and returning to point of origin, where the inter-area distance is symmetric and known. This real world application is a deceptive simple combinatorial problem and our approach is to develop solutions based on the idea of local search and meta-heuristic. As a standard problem, we have chosen a solution which is deceptively simple combinatorial problem and we defined it simply as the time spends or distance travelled by salesman visiting n cities (or nodes) cyclically. In one tour the students visits each area just once and finishes up where he started. As standard problems, we have chosen TSP with different areas visited once. This research presents the development of solution engine based on local search method known as Simulated Annealing as the initial solution and further use to improve the search and provide the best solution. A user friendly optimization program developed using Microsoft C++ to solve the TSP