Integrating route optimisation with vehicle and unloading dock scheduling in LCL cargo collection

Xuefei Liu, Meifeng Luo, Yifei Zhao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Less container load (LCL) has become an increasingly important element in containerised cargo export, due to the involvement of numerous small and medium size enterprises. Traditional cargo collection and consolidation processes are extremely complex and inefficient, which provides an excellent opportunity for improvement through integration. In this paper, we design a two-stage model comprising vehicle route optimisation for cargo collection and vehicle and unloading dock scheduling. In the first stage, namely, the route optimisation model, the Clarke-Wright saving algorithm is used, with the objective of minimising the total transport cost for a given shipment size, weight, and capacity constraint of cargo collection vehicles. In the second stage, the scheduling of both collection vehicles and unloading dock are modelled, using two sub-models for given constraints on the time window of the unloading docks and cargo collection routes. An application of this integrated model is illustrated based on the cargo collection problems in the hinterland of Shanghai port.

Original languageEnglish
Pages (from-to)262-280
Number of pages19
JournalInternational Journal of Shipping and Transport Logistics
Volume11
Issue number2-3
DOIs
Publication statusPublished - 1 Jan 2019

Keywords

  • Cargo collection
  • Integrated scheduling
  • LCL
  • Less container load
  • Route optimisation
  • Unloading dock scheduling
  • Vehicle dispatching

ASJC Scopus subject areas

  • Business and International Management
  • Transportation
  • Management Science and Operations Research
  • Management of Technology and Innovation

Fingerprint

Dive into the research topics of 'Integrating route optimisation with vehicle and unloading dock scheduling in LCL cargo collection'. Together they form a unique fingerprint.

Cite this