LAUSR

Service disruptions due to deliberate sabotage are serious threats to supply systems. To alleviate the loss of accessibility caused by such disruptions, identifying the system vulnerabilities that would be worth strengthening is a critical problem in critical infrastructure protection. Today's supply systems tend to be organized in a decentralized manner, with different components belonging to different entities, keeping much information private. Therefore, a protection plan must balance its benefits among these entities for universal agreement to be reached. This paper addresses the issue of decentralized supply chain fortification by proposing the R-Interdiction Median problem with Fortification for Decentralized supply systems (D-RIMF). In the D-RIMF, each demand node is private and is a client of a certain facility; each facility evaluates its potential worst-case reduction in accessibility, measured as the increase in service provision costs considering only its own clients, and the objective is to minimize the largest evaluation values. To model the D-RIMF, we introduce a bilevel multiagent framework, in which all facilities and the defender are considered as independent agents. To solve the D-RIMF, both heuristic and optimal algorithms are designed to satisfy different requirements. Finally, the usefulness of the D-RIMF and the performances of the proposed algorithms are observed through simulations performed on typical datasets.