Expectation and fractile models for decentralised distribution systems under demand uncertainty and their computational methods
Ichiro Nishizaki,
Tomohiro Hayashida,
Shinya Sekizaki and
Naomichi Tani
International Journal of Operational Research, 2024, vol. 50, issue 4, 446-476
Abstract:
In this study, we deal with the expectation and the fractile models for obtaining a Nash equilibrium point of the two-stage game for describing the competition and cooperation in decentralised distribution systems with stochastic demands, and develop computational methods. In the first stage of the equilibrium problem, each retailer independently determines the inventory level, and in the second stage for the coordination of retailers, the addition profit arising from the transshipment of the leftover inventories of all the retailers is maximised. Formulating the transshipment of the leftover inventories as a two-stage programming problem with simple recourse, we define an allocation rule based on the optimal dual solution of the transshipment problem which belongs to the core of the cooperative game. Using numerical examples, we demonstrate the effectiveness of the expectation and the fractile models, and examine the validity of their computational methods.
Keywords: decentralised distribution systems; equilibrium points; expectation and fractile models; two-stage games; computational methods. (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=140479 (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:ids:ijores:v:50:y:2024:i:4:p:446-476
Access Statistics for this article
More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().