Critical infrastructure location under supporting station dependencies considerations

This paper develops a framework to locate critical infrastructure (CI) facilities to most fully capitalize on the supporting stations (SSs) they depend on for normal operation. CI facilities include health services, transportation and electricity; agencies that impact the national economy, security and the public's health and wellbeing. SSs are facilities that provide essential services for the regular operation of a CI. For instance, the power service, communication services and water supply services are SSs for Hospitals. In this paper SSs are independent from the CIs that they service and have a heterogeneous probability of failure that will cripple the dependent CI. The proposed framework ranks the SS according to its cost of providing service such that the rank-1 SS is the primary service provider and incorporates the probability of failure for the SS. The CI will be served from secondary SS if the primary fails due to a disaster. This formulation insures the continuous service to the CI from SS and determines both the optimal location of the CI and the optimal number of demands served. A mixed integer linear programming approach is applied to develop a Reliable Facility Location Problem considering Supporting Stations (RFLP-SS) to identify the optimal location to build a critical facility. In addition to that, The RFLP-SS determines the capacity of the optimally located facility and its allocated demands. This research highlights the importance of considering dependencies among the SSs that service CI. The paper presents a case study in Puerto Rico to demonstrate the applicability of the proposed framework. The case study investigates the status of health services in Puerto Rico, and identifies the optimal locations to establish new hospitals. The paper recommends 11 locations for new hospitals so that the people of Puerto Rico will be better served than they are currently.