Modeling the Effects of Disinformation Spread on Multi-Commodity Networks

dc.contributor.advisor	Barker, Kash
dc.contributor.author	Rohrbach, Lily
dc.contributor.committeeMember	Zhu, Rui
dc.contributor.committeeMember	Gonzalez Huertas, Andres
dc.date.accessioned	2022-05-03T20:05:34Z
dc.date.available	2022-05-03T20:05:34Z
dc.date.issued	2022-05
dc.date.manuscript	2022
dc.description.abstract	Disinformation has become a more common weapon amidst growing social media platforms and users, targeting consumer behavior to affect physical infrastructure. Understanding how disinformation could attack a multi-commodity network and how to minimize its spread will help alleviate stress on systems during attacks. This research integrates an epidemiological model (SIR) with a mixed integer programming (MIP) model to minimize weighted shortage across commodities, evaluating the change over time dependent on disinformation spread β and recovery γ. It is then applied to a multi-commodity Swedish railway network carrying 14 goods over 200 nodes. Results demonstrated how different spread and recovery rates change the degree and timing of shortage.	en_US
dc.identifier.uri	https://hdl.handle.net/11244/335485
dc.language	en_US	en_US
dc.subject	disinformation	en_US
dc.subject	multi-commodity	en_US
dc.subject	SIR	en_US
dc.subject	mixed integer programming	en_US
dc.thesis.degree	Master of Science	en_US
dc.title	Modeling the Effects of Disinformation Spread on Multi-Commodity Networks	en_US
ou.group	Gallogly College of Engineering::School of Industrial and Systems Engineering	en_US