A Nature Inspired Approach to Solve Dynamic Traveling Salesman Problem

There are varieties of problems in various engineering branches which can’t be solved using traditional search techniques. These problems are known as NP hard problems. The problem which can’t be solved in a polynomial time is called a NP hard problem. This type of problem normally involved exhaustive searching in side it. Various Nature inspired techniques are developed and employed by the researchers to solve this kind of problems. Evolutionary algorithms (EAs) are one of them. These algorithms are known as optimization algorithms as they give very near optimal solution. In this paper, we investigate the ability of Evolutionary Algorithm (EA) by applying it to Dynamic Traveling Salesman Problem (DTSP). Dynamic Traveling Salesman Problem is a real world TSP where problem changes itself over the period of the time. It is very difficult to solve it by using traditional methods. We apply an optimization method, evolutionary algorithm to it and obtain the results. Experimental results indicate that EAs can overcome many problems encountered by traditional search techniques. The performance of EAs is compared to the results of traditional search techniques.