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The tragic events of 9/11 and the concerns about the potential for a terrorist or hostile state attack with weapons of mass destruction have led to an increased emphasis on risk analysis for homeland security. Uncertain hazards (natural and engineering) have been successfully analyzed using probabilistic risk analysis (PRA). Unlike uncertain hazards, terrorists and hostile states are intelligent adversaries who can observe our vulnerabilities and dynamically adapt their plans and actions to achieve their objectives. This article compares uncertain hazard risk analysis with intelligent adversary risk analysis, describes the intelligent adversary risk analysis challenges, and presents a probabilistic defender-attacker-defender model to evaluate the baseline risk and the potential risk reduction provided by defender investments. The model includes defender decisions prior to an attack; attacker decisions during the attack; defender actions after an attack; and the uncertainties of attack implementation, detection, and consequences. The risk management model is demonstrated with an illustrative bioterrorism problem with notional data.
In counterterrorism risk management decisions, the analyst can choose to represent terrorist decisions as defender uncertainties or as attacker decisions. We perform a comparative analysis of probabilistic risk analysis (PRA) methods including event trees, influence diagrams, Bayesian networks, decision trees, game theory, and combined methods on the same illustrative examples (container screening for radiological materials) to get insights into the significant differences in assumptions and results. A key tenent of PRA and decision analysis is the use of subjective probability to assess the likelihood of possible outcomes. For each technique, we compare the assumptions, probability assessment requirements, risk levels, and potential insights for risk managers. We find that assessing the distribution of potential attacker decisions is a complex judgment task, particularly considering the adaptation of the attacker to defender decisions. Intelligent adversary risk analysis and adversarial risk analysis are extensions of decision analysis and sequential game theory that help to decompose such judgments. These techniques explicitly show the adaptation of the attacker and the resulting shift in risk based on defender decisions.
In 2001, Congress enacted legislation that required a 2005 Base Realignment and Closure (BRAC) round to realign military units, remove excess facility capacity, and support defense transformation. The United States Army used multiple-objective decision analysis to determine the military value of installations and an installation portfolio model to develop the starting point to identify potential unit realignments and base closures, providing the basis for all recommendations. Ninety-five percent of the army’s recommendations were accepted by the BRAC 2005 Commission. The army expects these recommendations to create recurring savings of $1.5 billion annually after completion of BRAC implementation. This paper offers four contributions to decision analysis literature: an instructive application of multiple-objective decision analysis methods to portfolio selection, a useful method for constructing scales for interdependent attributes, a new method for assessing weights that explicitly considers importance and variation (Swing Weight Matrix), and practical advice on how to use multiple-objective decision analysis methods in a complex and controversial political environment.
Air Force 2025 was a study directed by the Chief of Staff of the United States Air Force to identify key system concepts and technologies for achieving air and space dominance in the year 2025. The study was a large effort in which over 200 military experts participated for more than one year. We developed a Value-Focused Thinking model, which we used to evaluate which futuristic system concepts have the greatest potential to ensure future U.S. air and space dominance. We named the value model Foundations 2025 because it represented a return to the basics of air and space dominance. We used the "silver standard" approach for value hierarchy development. The participants identified key verbs to describe tasks that must be performed in 2025 to ensure air and space dominance. The value hierarchy was developed bottom-up by aggregating these verbs into higher order tasks using affinity diagrams. Using the value hierarchy, we used multiattribute decision analysis techniques to develop an additive value model with 134 attributes. The Foundations 2025 value model was successfully used to score 43 futuristic system concepts and provide insights about the most promising system concepts and technologies. The analysis results directly supported the study director and the senior leadership of the United States Air Force.Decision Analysis, Value-Focused Thinking, Multiattribute Decision Analysis
This paper describes the use of multiple-objective decision analysis to qualitatively and quantitatively assess the quality of an endangered watershed and guide future efforts to improve the quality of the watershed. The Upham Brook Watershed is an urban watershed that lies at the interface of declining inner-city Richmond, Virginia, and growth-oriented Henrico County. A section of stream within the watershed has been identified as so dangerously polluted that it threatens the health of the residents who live within the watershed boundaries. With funding provided by the National Science Foundation, the Upham Brook Watershed project committee was formed to address the quality of the Upham Brook Watershed; it consisted of experts from multiple disciplines: stream ecology, environmental policy, water policy, ground and surface water hydrology and quality, aquatic biology, political science, sociology, citizen participation, community interaction, psychology, and decision and risk analysis. Each member's values and goals were brought together using a watershed management framework to meet the overall objective of the committee: to maximize the quality of the Upham Brook Watershed. The resulting model was used to identify the largest value gaps and to identify future programs needed to improve the quality of the watershed.
Criteria are the central focus of multi‐criteria decision analysis. Many authors have suggested using our values (or preferences) to define the criteria we use to evaluate alternatives. Value‐focused thinking (VFT) is an important philosophy that advocates a more fundamental view of values in our decision making in our private and professional lives. VFT proponents advocate starting first with our values and then using our values to create decision opportunities, evaluate alternatives and finally develop improved alternatives. It has been 20 years since VFT was first introduced by Ralph Keeney. This paper surveys the VFT literature to provide a comprehensive summary of the significant applications, describe the main research developments and identify areas for future research. We review the scope and magnitude of VFT applications and the key developments in theory since VFT was introduced in 1992 and found 89 papers written in 29 journals from 1992 to 2010. We develop about 20 research questions that include the type of article (application, theory, case study, etc.), the size of the decision space (which, when given, ranged from $200K to billions of dollars), the contribution documented in the article (application benefits) and the research contributions (categorized by preferences, uncertainties and alternatives). After summarizing the answers to these questions, we conclude the paper with suggestions for improving VFT applications and potential future research. We found a large number of significant VFT applications and several useful research contributions. We also found an increasing number of VFT papers written by international authors. Copyright © 2012 John Wiley & Sons, Ltd.
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