A multi-stage stochastic model for designing a linked cross-docking distribution network with heterogeneous trucks

Saeid Nasrollahi (), Hasan Hosseini-Nasab (), Mohammad Bagher Fakhrzad () and Mahboobeh Honarvar ()
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Saeid Nasrollahi: Yazd University
Hasan Hosseini-Nasab: Yazd University
Mohammad Bagher Fakhrzad: Yazd University
Mahboobeh Honarvar: Yazd University

Operational Research, 2023, vol. 23, issue 1, No 15, 41 pages

Abstract: Abstract Designing an efficient supply chain network where supply capacity and demand change over periods has been a growing challenge for today’s transport systems. This paper addresses the problem of designing a three-echelon cross-docking distribution network with linked cross-docks to transport consolidated products by heterogeneous trucks under demand and supply capacity uncertainties. Two bi-objective multi-stage stochastic models are formulated to minimize the total costs of distribution network design and the total shortage of products. In model 1, homogeneous trucks and individual cross-docks are used without linking cross-docks, and in model 2, heterogeneous trucks with linking cross-docks are considered. The minimum deviation method is employed to unify the objective functions and obtain a single normalized objective function. Several simulated problems are solved by the branch and bound method to compare the proposed models. Results demonstrate that model 2 is more efficient than model 1 in designing a suitable cross-docking distribution network. Model 2 is then utilized to design an agri-food supply chain network in a real case study.

Keywords: Cross-docking; Distribution network design; Multi-stage stochastic model; Heterogeneous trucks; Consolidated products (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s12351-023-00762-0

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