A multi-stage algorithm for a capacitated vehicle routing problem with time constraints

The Vehicle Routing Problem (VRP) is one of the most optimized tasks studied and it is implemented in a huge variety of industrial applications. The objective is to design a set of minimum cost paths for each vehicle in order to serve a given set of customers. Our attention is focused on a variant of VRP, the capacitated vehicle routing problem when applied to natural gas distribution networks. Managing natural gas distribution networks includes facing a variety of decisions ranging from human resources and material resources to facilities, infrastructures, and carriers. Despite the numerous papers available on vehicle routing problem, there are only a few that study and analyze the problems occurring in capillary distribution operations such as those found in a metropolitan area. Therefore, this work introduces a new algorithm based on the Saving Algorithm heuristic approach which aims to solve a Capacitated Vehicle Routing Problem with time and distance constraints. This joint algorithm minimizes the transportation costs and maximizes the workload according to customer demand within the constraints of a time window. Results from a real case study in a natural gas distribution network demonstrates the effectiveness of the approach.