Districting for Parcel Delivery Services { A Two-Stage Solution Approach and a Real-World Case Study

Matthias Bendera, Jӧrg Kalcsics, Anne Meyer

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

This paper studies a real-world problem arising in the context of parcel delivery. Given a heterogeneous set of resources, i.e., different drivers and different vehicles, the problem for each day consists of assigning a driver and a vehicle to each customer requiring service. Two conflicting aspects must be taken into account. On the one hand, service consistency is desirable, meaning that a customer should always be served by the same driver. On the other hand, daily demand uctuations and tight resource constraints prohibit fxed resource assignments. With the aim of finding a reasonable compromise between these aspects, we propose a novel two-stage districting approach, which establishes delivery districts in the first stage and adapts them to the daily demand realizations in the second stage. For the first stage problem we propose three models that differ in the level of detail of their input data, their
expected compliance with service consistency and the driver's contractual working times, and their computational effort. Our two-stage approach merges the two dominant approaches in the literature, which either determine a priori routes and then adapt them on a daily basis, or derive fixed service regions for drivers. We present a case study based on a real-world data set. The results highlight the differences between the three first stage models and show that only few adaptations of the districts are necessary in the second stage to achieve feasible daily delivery tours along with a very good workload balance for drivers. We also analyze the effects of a homogeneous vs a heterogeneous fleet, of full time drivers vs full and part time drivers, and of the location of the depot and the length of the planning horizon.
Original languageEnglish
Article number102283
Number of pages44
Early online date28 May 2020
Publication statusPublished - 31 Oct 2020


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