A decision support system for optimizing dynamic courier routing operations

• Propose a dynamic courier routing model with new orders and order cancellation.
• Integrate fuzzy time windows to formulate and evaluate courier service level.
• Develop a Hybrid Neighboring Search algorithm to tackle the dynamic problem.
• Enhance service level without increasing transportation and manpower cost.

In this paper, we propose a prototype of a decision support system (DSS) that integrates a hybrid neighborhood search algorithm to solve the offline and online routing problems arising in courier service. In the dynamic operational environment of courier service, new customer orders and order cancellations continually arrive over time and thus disrupt the optimal routing schedule that was originally designed. This calls for the real-time re-optimization of routes. As service level is sensitive to whether allowable service time intervals are wide or narrow, it is valuable to study how adjustable and flexible time windows influence the courier service efficiency in a dynamic environment. To capture these dynamic features, a dynamic vehicle routing problem (DVRP) that simultaneously considers new customer orders and order cancellations is investigated in this study. Meanwhile, fuzzy time windows are formulated in the DVRP model to quantify the service level and explore the service efficiency. To tackle the new problem, we propose a competitive hybrid neighborhood search heuristic for (re)optimizing the offline and online routes. Numerical computational experiments and the comparison with results from Lingo show that our algorithm is capable of re-optimizing dynamic problems effectively and accurately in a very short time. The proposed model and algorithms are able to enhance courier service level without further expense of a longer traveling distance or a larger number of couriers.