A case study of Consistent Vehicle Routing Problem with Time Windows

TL;DR

This paper presents a heuristic for the ConVRPTW, a vehicle routing problem with time windows and driver consistency, demonstrating improved routing efficiency and service levels in real-world food distribution scenarios.

Contribution

The paper introduces a heuristic specifically designed for ConVRPTW, addressing irregular customer demands and driver assignment constraints, with validation on real-world data.

Findings

Heuristic outperforms MILP on small instances.

Significant reduction in number of vehicles used.

Higher percentage of orders delivered on time.

Abstract

We develop a heuristic for the Consistent Vehicle Routing Problem with Time Windows (ConVRPTW), which is motivated by a real-world application at a food company's distribution center. Besides standard VRPTW restrictions, ConVRPTW assigns each customer just one driver to fulfill their orders during the whole multi-period planning horizon. For each driver and period, a route is sought to serve all their customers with positive demand. For each customer, the number of periods between consecutive orders and the ordered quantities are highly irregular. This causes difficulties in the daily routing, negatively impacting the service level of the company. Similar problems have been studied as ConVRP, where the number of drivers is fixed a priori, and only the total travel time is minimized. Moreover, the clients present no time window constraints, but the visits should be scheduled with a small arrival time variation. In our model, the objective is to minimize the number of drivers. We impose hard time windows but do not consider time consistency in more detail. We compare solutions given by the heuristic with solutions of a MILP model on a set of small artificial instances and solutions used by the food company on real-world instances. The results show the effectiveness of the heuristic. For the company, we obtain significant improvements in the routing plans, with a lower number of vehicles and a higher rate of orders delivered within the prescribed time window.