Developing a Stochastic Two-Tier Architecture for Modelling Last-Mile Delivery and Implementing in Discrete-Event Simulation

Zichong Lyu, Dirk Pons, Jiasen Chen, Yilei Zhang

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Modelling freight logistics is challenging due to the variable consignments and diverse customers. Discrete-event Simulation (DES) is an approach that can model freight logistics and incorporate stochastic events. However, the flexible delivery routes of Pickup and Delivery (PUD) are still problematic to simulate. This research aims to develop last-mile delivery architecture in DES and evaluate the credibility of the model. A two-tier architecture was proposed and integrated with a DES model to simulate freight operations. The geographic foundation of the model was determined using Geographic Information Systems (GIS), including identifying customer locations, finding cluster centres, and implementing Travelling Salesman Problem (TSP) simulation. This complex model was simplified to the two-tier architecture with stochastic distances, which is more amenable to DES models. The model was validated with truck GPS data. The originality of the work is the development of a novel and simple methodology for developing a logistics model for highly variable last-mile delivery.

Original languageEnglish
Article number214
JournalSystems
Volume10
Issue number6
DOIs
Publication statusPublished - 10 Nov 2022
Externally publishedYes

Keywords

  • discrete-event simulation
  • freight operations
  • geographic information systems
  • last-mile delivery

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