Abstract

Urban freight deliveries are often subject to many access restrictions which creates the need to establish a system of loading bays and to split the last mile delivery into driving and walking parts. A new model based on hard and soft clustering approach is developed to solve the loading bay assignment problem for efficient vehicle routing and walking in last mile delivery. The flexibility of the model is provided by the soft clustering approach based on different membership degrees of customers to loading bays. Especially for instances with large numbers of loading bays, soft clustering seems to give better results, it leads to higher flexibility of city logistics systems, minimal driving distances, and adequately short walking paths, which contribute to the goal of reaching sustainable urban freight deliveries.

Highlights

  • In Europe, 72% of people live in cities, and this percentage is expected to rise to 80% by 2050 [1]

  • Urban freight deliveries are often subject to many access restrictions which creates the need to establish a system of loading bays and to split the last mile delivery into driving and walking parts

  • An open question arises—where and how many loading bays should we provide to perform this transshipment and execute last mile delivery in the most efficient way

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Summary

Introduction

In Europe, 72% of people live in cities, and this percentage is expected to rise to 80% by 2050 [1]. Cities are experiencing a growing demand for transport with increasing congestion, noise, emissions, and other negative effects of transport on the environment and city dwellers [3,4]. These problems are most prevalent in historical cities and city centers, which are generally not designed to cope with such high traffic volumes. Cities are further hampered by the modern trends of just-in-time delivery and e-commerce, which increase the number of deliveries and lead to fragmentation of urban freight transport [6,7]. Studies show that lorries account for 15% of urban traffic and more than 20% of CO2 emissions and congestion [9]

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