An approach to dynamic traveling salesman problem
Most researches in evolutionary computation focus on the optimization of static and no-change problems. Many real world optimization problems however are actually dynamic, and optimization methods capable of continuously adapting the solution to a changing environment are needed. In this paper, we introduce an approach to solving the dynamic TSP. A dynamic TSP is harder than a general TSP, which is a NP-hard problem, because the city number and the cost matrix of a dynamic TSP are time varying. We propose an algorithm to solve the dynamic TSP problem, which is the hybrid of EN and inver-over algorithm. From the results of the experiment, we conclude this algorithm is effective.