Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98288
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Title: Integrating route optimisation with vehicle and unloading dock scheduling in LCL cargo collection
Authors: Liu, X 
Luo, M 
Zhao, Y
Issue Date: 2019
Source: International journal of shipping and transport logistics, 2019, v. 11, no. 2-3, p. 262-280
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.
Keywords: Cargo collection
Integrated scheduling
LCL
Less container load
Route optimisation
Unloading dock scheduling
Vehicle dispatching
Publisher: InterScience
Journal: International journal of shipping and transport logistics 
ISSN: 1756-6517
EISSN: 1756-6525
DOI: 10.1504/IJSTL.2019.099273
Rights: © 2019 Inderscience Enterprises Ltd.
This is the accepted manuscript of the following article: Liu, X., Luo, M., & Zhao, Y. (2019). Integrating route optimisation with vehicle and unloading dock scheduling in LCL cargo collection. International Journal of Shipping and Transport Logistics, 11(2-3), 262-280, which has been published in final form at https://doi.org/10.1504/IJSTL.2019.099273.
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