EconPapers    
Economics at your fingertips  
 

Robust Supply Chain Network Equilibrium Model

Tatsuya Hirano () and Yasushi Narushima ()
Additional contact information
Tatsuya Hirano: FUJITSU FIP Corporation, Tokyo, 105-8668 Japan
Yasushi Narushima: Faculty of International Social Sciences, Yokohama National University, Hodogaya-ku, Yokohama, 240-8501 Japan

Transportation Science, 2019, vol. 53, issue 4, 1196–1212

Abstract: An important and often researched area of management science is mathematical modeling of a supply chain. Competitive situations can occur in supply chains owing to the involvement of multiple decision makers (players) that independently decide their behaviors. To investigate competitive supply chain networks, a supply chain network equilibrium (SCNE) model was proposed. Recently, particular attention has been paid to risk management of a supply chain. In equilibrium models, it is vital to consider players’ decisions and interdependence relations. Thus, we consider competitive supply chain networks with uncertainties in the other players’ strategies. In the proposed model, each player cannot know exactly the other players’ strategies, and they decide their strategy using the minimax principle (that is, assuming the worst case). We call it the robust SCNE model. We formulate the robust SCNE model as a variational inequality problem (VIP) in which the set associated with the VIP is constructed by second-order cone constraints. We show the existence and uniqueness of the equilibrium under mild assumptions. In addition, we give, in a special case, some relations between players’ strategies in the equilibrium and magnitudes of uncertainties. Finally, some numerical results are provided.

Keywords: transportation; supply chain network equilibrium model; robust optimization; variational inequality problem; existence and uniqueness (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://doi.org/10.1287/trsc.2018.0843 (application/pdf)

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:inm:ortrsc:v:53:y:2019:i:4:p:1196-1212

Access Statistics for this article

More articles in Transportation Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().

 
Page updated 2025-03-19
Handle: RePEc:inm:ortrsc:v:53:y:2019:i:4:p:1196-1212