Application of fuzzy sets in decision analysis for prioritising critical energy infrastructures

This paper presents an approach for long-range decision-making in the domain of critical infrastructure using subjective information. Critical infrastructures provide goods and services essential to public wellbeing, including public safety, economic vitality, and security. Infrastructure owners, operators, and policy-makers have to make decisions related to fulfilling stakeholder needs. These decisions are routinely made in a landscape marked by ambiguity, complexity, unpredictability, and uncertainty associated with future states of infrastructure systems and their environment. In this paper, the authors suggest that fuzzy set theory could be used to enhance decision-making since it can account for unknown possible system states along any array of parameters. Specifically, this paper uses fuzzy sets to rank and prioritise three energy alternatives using five evaluation parameters and a possible infrastructure state of resiliency. A general model is developed that could be used to support a long-range decision process. The model can be adapted and deployed in other sectors in the domain of critical infrastructures.