A rolling horizon approach for a multi-stage stochastic fixed-charge transportation problem with transshipment

Rossana Cavagnini, Luca Bertazzi and Francesca Maggioni

European Journal of Operational Research, 2022, vol. 301, issue 3, 912-922

Abstract: We study a fixed-charge transportation problem under stochastic and dynamic demand. We propose a multi-stage mixed integer stochastic programming formulation, where the first-stage decision is the delivery from the supplier to the retailers, while transshipment is used, in addition to classical backordering as recourse decision. The objective is the minimization of the total expected cost. We prove that this problem is NP-hard and, through a worst-case analysis, that transshipment can provide significant cost savings. Extensive computational studies are carried out to evaluate the performance of a rolling horizon approach with respect to the optimal cost. Numerical results show that this heuristic provides effective solutions in short computational time. Managerial insights are finally drawn.

Keywords: Logistics; Fixed-charge transportation problem; Transshipment; Multi-stage stochastic programming; Rolling horizon approach (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221721009887
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:301:y:2022:i:3:p:912-922

DOI: 10.1016/j.ejor.2021.11.037

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().