Solving Vehicle Routing Problem with Time Window Constraints

This paper proposes a heuristic, Tabu-Disturbance Algorithm (TDA), to efficiently and effectively solve Vehicle Routing Problem with Time Window Constraints (VRPTW). TDA integrates Tabu Search (TS) and Noising Method (NM). TS is one of the most popular generic heuristics in solving VRPHTW in recent years and NM is a combinatorial optimization meta-heuristic. The first objective is to determine the route that minimizes the total vehicle travel distances. This leads to a quick response to satisfy customer demands. The second objective is to find the minimum required number of vehicles. This can reduce the transportation cost. TDA results in good solution quality by the evaluation of Solomon's benchmark instances. Comparing with the optimal solution of the partial instances obtained by Desrochers et al. (1992), the average deviation of distance is about 1.0% and the average deviation of number of vehicles is about 2.4%, compared to the known "best" solutions.