Solving Vehicle Routing Problem with Considering Traffic Congestion Using Tabu Search Algorithm

The increasing population in urban areas has resulted in increasing challenges faced by large cities in the world to design effective and efficient transportation systems, both for people and goods. The increasingly severe traffic conditions in urban areas make the situation even more difficult. As the number of vehicles of various types increases, the level of congestion increases rapidly. This shows the importance of considering traffic congestion in designing logistics systems in urban areas. Although there are many studies on vehicle routing problems (VRP), those that consider congestion are still limited. This study aims to solve a VRP by considering traffic congestion using a heuristic method based on the Tabu Search algorithm. Tabu Search (TS) is a type of metaheuristic. The success of TS is due to its ability to direct the search process so as not to get trapped in the local optimum, in large part, like many other metaheuristics. It has been widely used to solve complex combinatorial optimization problems. The performance of the solution resulted from this study shows that compared to the commercial solver, the heuristic can solve the VRP with a gap of 0.00%. It means that the proposed heuristic can result in optimal solutions for small data. For large data, the performance of the proposed heuristic is compared to the previous study. Compared to the previous study, the heuristic results in a better solution with 5% of improvement.