Optimized Solution of TSP (Travelling Salesman Problem) Based on Mendelian Inheritance

Background: TSP problem has been the part of literature from many decades; it’s an important optimization issue in operation research. TSP problem always remain greedy for the better results especially if chosen working field are Genetic Algorithms (GA). Objective: This paper presents a TSP solution, which performed the modified selection and crossover operations as well as takes advantage of Mendelian inheritance while producing the generations. Methods: GA has very broad resolution scope for optimization problems and it is capable enough for generating well-optimized results if right GA technique has been applied on right point of issue in controlled manner. here the proposed agenda is to utilize the GA concept for TSP by applying mendels rules which is never applied before for the same issue. Here the proposed scheme applies some modification in traditional Mendel process. In general, full chromosome window has been utilized in mendel inheritance process but in presented scheme we have utilizes Most Significant Bits (MSB) only which helps in to control the convergence aptitude of the process. Results: The scheme uses advanced modified Mendel operation which helps in to control convergence aptitude of the operation. It efficiently minimizes the total travelled distance of the graph which was the ultimate objective of the problem and that has been successfully achieved. Conclusion: The validation of the scheme has been confirmed from the obtained results, which are better enough as comparison to traditional TSP-GA.