Marousi, Asimina;
Thyagarajan, Karthik;
Pinto, Jose M;
Papageorgiou, Lazaros G;
Charitopoulos, Vassilis M;
(2024)
A Nash equilibrium approach to supply chain design of oligopoly markets under uncertainty.
In: Manenti, Flavio and Reklaitis, Gintaras V, (eds.)
Computer Aided Chemical Engineering.
(pp. 643-648).
Elsevier: Amsterdam, The Netherlands.
![]() |
Text
495Marousi.pdf - Accepted Version Access restricted to UCL open access staff Download (423kB) |
Abstract
An increased interest has been observed by the process systems community for the integration of game theoretic principles to the design and operation problems, especially of supply chains. This integration can achieve a better insight to the problem at hand and at the same time build resilience. In this work we aim to further increase the stability of a supply chain design problem by taking into account uncertainty. An oligopoly Nash bargaining game is proposed under a scenario-based approach in order to fairly allocate the profit among the members of a duopoly industrial gas market. The nonlinearity stemming from the Nash objective is linearised by a piecewise SOS2 linear approximation resulting in an MILP class. The design of the scenario-based approach is compared with that of the deterministic case for a number of sampled uncertainty realisations. Results suggest that the scenario-based approach can better leverage the capacity potential of the duopoly while guaranteeing higher profits and maintaining the market share of the initial market.
Type: | Book chapter |
---|---|
Title: | A Nash equilibrium approach to supply chain design of oligopoly markets under uncertainty |
ISBN-13: | 9780443288241 |
DOI: | 10.1016/B978-0-443-28824-1.50108-3 |
Publisher version: | http://dx.doi.org/10.1016/b978-0-443-28824-1.50108... |
Language: | English |
Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Game theory; Nash bargaining; supply chain optimisation; uncertainty; scenario-based optimisation |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10194768 |
Archive Staff Only
![]() |
View Item |