In-transit freight consolidation of indivisible shipments

Abdulkader S. Hanbazazah, Luis E. Castro, Murat Erkoc and Nazrul I. Shaikh

Journal of the Operational Research Society, 2020, vol. 71, issue 1, 37-54

Abstract: This paper studies the multi-period freight consolidation problem for a third-party logistics (3PL) provider that transships multiple products from multiple suppliers to a single end customer. The shipments are first transported to select consolidation terminals where the 3PL provider aims to consolidate the inbound shipments so as to reduce costs. This imposes a complex decision problem to the 3PL provider since consolidation may require that the inbound shipments spend more time at the terminals, whereas all shipments have prespecified pickup dates and delivery deadlines. Moreover, the shipments picked up from the suppliers are indivisible, that is, a shipment cannot be split into multiple lots and assigned to separate routes. This paper presents a mixed-integer linear programming model and proposes a heuristic for solving the resulting problem. The proposed heuristic partitions the multi-period problem into multiple subproblems by splitting the planning horizon into smaller mutually exclusive units which makes the planning problem relatively insensitive to the length of the planning horizon and hence scalable. The effectiveness of the proposed heuristic is demonstrated via a real-life problem: a close-to-optimal solution for a 360-day planning problem that could not be solved using commercial solvers due to its size is obtained within two hours.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/01605682.2018.1527191 (text/html)
Access to full text is restricted to subscribers.

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:taf:tjorxx:v:71:y:2020:i:1:p:37-54

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjor20

DOI: 10.1080/01605682.2018.1527191

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald

More articles in Journal of the Operational Research Society from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().