Location flexibility in parcel delivery operations: framework and empirical analysis

Dmitry Krushinsky,Xuezhen Guo,G D H Claassen

doi:10.1093/imaman/dpab004

Dmitry Krushinsky, Xuezhen Guo + Show 1 more

Open Access

https://doi.org/10.1093/imaman/dpab004

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Abstract

Abstract In traditional parcel delivery operations, customers determine delivery locations and, hence, the performance of a transporter. We exploit this idea and show that customers can improve the efficiency of a transporter by giving the latter flexibility in choosing the delivery locations. Two possible policies to enable this flexibility are presented and evaluated. The first policy, conceptually similar to roaming vehicle routing, is related to the presence of alternative locations. The second policy is related to the possibility of aggregating/skipping some locations. We show that route optimization behind both policies can be modelled via the well-known generalized travelling salesman problem. Extensive computational experiments with real parcel delivery data are performed to evaluate the potential of the presented policies and to obtain insights for possible implementation in daily practice. The experiments show that under certain conditions, the two proposed policies can lead to 15 to 20% improvement in the route length and in extreme yet realistic cases up to 40 to 50%. Consequently, the concept of flexible delivery locations has potential for practice, especially in densely populated areas.

Highlights

After many years of a double-digit growth, the global turnover of business-to-customer e-commerce reached EUR 19.43 billion in 2015 (Kalinicet al., 2016)
We present two policies leading to a win–win situation—more space for traffic optimization and an additional reward for the customers at the same time
The location flexibility can be seen as a special case of the more general concept of customers engagement

Summary

Introduction

After many years of a double-digit growth, the global turnover of business-to-customer e-commerce reached EUR 19.43 billion in 2015 (Kalinicet al., 2016). The rise of e-commerce leads to high fragmentation of shipments (Esser & Kurte, 2013; Schewel & Schipper, 2012), resulting in an unprecedented high number of parcel deliveries in last miles. In today’s highly demanding environment, establishing an efficient last-mile parcel delivery network is a very challenging task, as confirmed by Gevaers et al (2011) who claim that last-mile delivery is usually the least efficient part of supply chains. It is considered one of the most expensive

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