Bayesian Stackelberg game model for water supply networks against interdictions with mixed strategies
J. Jiang and
X. Liu
International Journal of Production Research, 2021, vol. 59, issue 8, 2537-2557
Abstract:
We address a problem of preventing an interdiction on water supply networks by building a Bayesian Stackelberg game model involving stakeholders of a defender and an interdictor. The defender initiates to allocate resource to network components to make a trade-off between network resilience measured by water satisfaction rate and the defender's cost, whereas the interdictor follows to interdict a component with the objectives of maximising the destruction level on the network structure and minimising the interdictor's cost. Specifically, the defender adopts mixed defence strategies, which implies that the interdictor is uncertain of the defender's resource allocation. Moreover, we propose sufficient conditions for the elimination of the dominated defence and interdiction strategies. A decomposed iterative learning algorithm (DILA) and a smallest-depth binary-partition based hierarchical algorithm (SBHA) are developed to reduce the sizes of the defence and interdiction strategy sets, respectively, thus analysing the optimal mixed defence strategies. Finally, a real case study with private information is conducted, thus providing valuable suggestions for the defender's resource allocation against interdictions.
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2020.1735661 (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:59:y:2021:i:8:p:2537-2557
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2020.1735661
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 ().