Allocation of Resources for Protecting Public Goods against Uncertain Threats Generated by Agents

Interim Reports on work of the International Institute for Applied Systems Analysis receive only limited review. Views or opinions expressed herein do not necessarily represent those of the Institute, its National Member Organizations, or other organizations supporting the work. ii Foreword This report describes the research the author advanced during her participation in the 2010 Young Scientists Summer Program (YSSP) with the Integrated Modeling Environment Project. The aim of this research is to build up a framework supporting robust decision-making for protecting public goods against uncertain threats generated by agents and chances. Under increasing interdependencies of globalization processes the protection of public goods is becoming a critical topic, especially against uncertain threats generated by agents. Examples include both direct threats such as terrorist attacks, recent BP oil spill, and financial crisis, and indirect threats associated with natural disasters such as improper land use planning and cascading risk management at a disaster prone area. This work builds up a framework for such a broad class of decision problems with inherent uncertainties and strategic responses. The framework combines the " leader-follower " game concept with approaches of stochastic optimization and multicriteria analysis. It incorporates both mathematical models and computational algorithms for public goods protection against uncertain and endogenous threats, which makes it ready for realistic applications. In particular, two case studies are presented, including defending urban areas against uncertain intentional attacks and regulating electricity networks with consideration of possible outages. The research conducted during the three-month YSSP period will be continued by advancing the theoretical framework and its practical applications. Abstract This paper analyses a framework for designing robust decisions against uncertain threats to public goods generated by multiple agents. The agents can be intentional attackers such as terrorists, agents accumulating values in flood or earthquake prone locations, or agents generating extreme events such as electricity outage and recent BP oil spill, etc. Instead of using a leader-follower game theoretic framework, this paper proposes a decision theoretic model based on two-stage stochastic optimization (STO) models for advising optimal resource allocations (or regulations) in situations characterized by uncertain perceptions of agent behaviors. In particular, the stochastic mini-max model and multi-criteria STO model are presented to solve for two different types of protection decisions for public goods security. Furthermore, the use of conditional value at risk (or expected shortfalls) is advanced in the context of quantile optimization for dealing with potential extreme events. Proposed …