Decentralised decision-making in a multi-party supply chain
Anu Thomas,
Mohan Krishnamoorthy,
Jayendran Venkateswaran and
Gaurav Singh
International Journal of Production Research, 2016, vol. 54, issue 2, 405-425
Abstract:
In this paper, we consider multi-party coordination in a supply chain (SC) that consists of a set of independent producers and a set of resource managers. A decentralised decision-making approach is proposed for a coal SC, with three independent parties -- multiple mines, a rail operator and a terminal. The rail operator and the terminal act as common resource managers and connects the independent mines via a rail network. The objective of this SC is to efficiently use an independent rail operator to transport coal from different mines to meet the shipping demand at the terminal. The underlying coordination problem can be seen as a multi-resource constrained scheduling problem. A major part of this paper addresses the key challenges in a decentralised approach based on column generation (CG), which are to compute the value of a column, better upper bounds and to update the multipliers using decentralised methods. We have also discussed the mathematical models for different decision units, the CG algorithm and different strengthening methods. A comprehensive computational experiment based on randomly generated instances highlights the effect of decentralisation and the value of information-sharing. The proposed solution approaches can be extended to a multi-party case with any number of common resources.
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2015.1096977 (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:tprsxx:v:54:y:2016:i:2:p:405-425
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2015.1096977
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().