Book contents
- Improving Homeland Security Decisions
- Improving Homeland Security Decisions
- Copyright page
- Contents
- Contributors
- 1 Improving Homeland Security Decisions
- 2 Probabilistic Risk Analysis and Terrorism Risk
- 3 Integrating Stakeholder Values into Strategic Planning through Comparative Risk Analysis
- 4 Validating Terrorism Risk Assessment Models – Lessons Learned from 11 Models
- 5 Coping with Uncertainty in Adversarial Risk Analysis
- 6 A Risk and Economic Analysis of Dirty Bomb Attacks on the Ports of Los Angeles and Long Beach
- 7 Regional Transportation and Supply Chain Modeling for Large-Scale Emergencies
- 8 Economic Consequences of Terrorism and Natural Disasters: The Computable General Equilibrium Approach
- 9 Economic Resilience to Terrorism and Natural Hazards
- 10 The Temporal Regional Economic Impacts of a Hurricane Disaster on Oil Refinery Operations: A FlexNIEMO Approach
- 11 Risk-Informed Benefit-Cost Analysis
- 12 Enhancing Post-disaster Economic Resilience: Public-Private Partnership for Insuring Terrorism
- 13 Economic Impacts of Changes in Wait Times at U.S. Ports of Entry
- 14 Organizational Decision Processes
- 15 A Value Model for Evaluating Homeland Security Decisions
- 16 Identifying, Structuring, and Comparing the Objectives of Al Qaeda and ISIL
- 17 Multi-objective Decision Making: Expected Utility vs. Some Widely Used (and Flawed) Methods
- 18 Achieving Multiple Objectives with Limited Resources: Using Utility Theory and Control Theory
- 19 Defender-Attacker Decision Tree Analysis to Combat Terrorism
- 20 Decision Making for Bioterror Preparedness: Examples from Smallpox Vaccination Policy
- 21 Stackelberg Security Games (SSG) Basics and Application Overview
- 22 Basic Solution Concepts and Algorithms for Stackelberg Security Games
- 23 Mixed-Integer Optimization Methods for Solving Stackelberg Security Games
- 24 Methods for Addressing the Unpredictable Real-World Element in Security
- 25 Learning to Play Stackelberg Security Games
- 26 Evaluating Deployed Decision Support Systems for Security: Challenges, Analysis, and Approaches
- 27 Homeland Security Resource Allocation Games: Considering Partially Strategic Attackers and Equity
- 28 Decision Analysis by Proxy for Adaptive Adversaries
- 29 Asymmetric Prescriptive/Descriptive Game Theory for Counterterrorism
- 30 Near-Misses and Decision Making Under Uncertainty in the Context of Cybersecurity
- Index
- References
17 - Multi-objective Decision Making: Expected Utility vs. Some Widely Used (and Flawed) Methods
Published online by Cambridge University Press: 13 December 2017
By
Book contents
- Improving Homeland Security Decisions
- Improving Homeland Security Decisions
- Copyright page
- Contents
- Contributors
- 1 Improving Homeland Security Decisions
- 2 Probabilistic Risk Analysis and Terrorism Risk
- 3 Integrating Stakeholder Values into Strategic Planning through Comparative Risk Analysis
- 4 Validating Terrorism Risk Assessment Models – Lessons Learned from 11 Models
- 5 Coping with Uncertainty in Adversarial Risk Analysis
- 6 A Risk and Economic Analysis of Dirty Bomb Attacks on the Ports of Los Angeles and Long Beach
- 7 Regional Transportation and Supply Chain Modeling for Large-Scale Emergencies
- 8 Economic Consequences of Terrorism and Natural Disasters: The Computable General Equilibrium Approach
- 9 Economic Resilience to Terrorism and Natural Hazards
- 10 The Temporal Regional Economic Impacts of a Hurricane Disaster on Oil Refinery Operations: A FlexNIEMO Approach
- 11 Risk-Informed Benefit-Cost Analysis
- 12 Enhancing Post-disaster Economic Resilience: Public-Private Partnership for Insuring Terrorism
- 13 Economic Impacts of Changes in Wait Times at U.S. Ports of Entry
- 14 Organizational Decision Processes
- 15 A Value Model for Evaluating Homeland Security Decisions
- 16 Identifying, Structuring, and Comparing the Objectives of Al Qaeda and ISIL
- 17 Multi-objective Decision Making: Expected Utility vs. Some Widely Used (and Flawed) Methods
- 18 Achieving Multiple Objectives with Limited Resources: Using Utility Theory and Control Theory
- 19 Defender-Attacker Decision Tree Analysis to Combat Terrorism
- 20 Decision Making for Bioterror Preparedness: Examples from Smallpox Vaccination Policy
- 21 Stackelberg Security Games (SSG) Basics and Application Overview
- 22 Basic Solution Concepts and Algorithms for Stackelberg Security Games
- 23 Mixed-Integer Optimization Methods for Solving Stackelberg Security Games
- 24 Methods for Addressing the Unpredictable Real-World Element in Security
- 25 Learning to Play Stackelberg Security Games
- 26 Evaluating Deployed Decision Support Systems for Security: Challenges, Analysis, and Approaches
- 27 Homeland Security Resource Allocation Games: Considering Partially Strategic Attackers and Equity
- 28 Decision Analysis by Proxy for Adaptive Adversaries
- 29 Asymmetric Prescriptive/Descriptive Game Theory for Counterterrorism
- 30 Near-Misses and Decision Making Under Uncertainty in the Context of Cybersecurity
- Index
- References
Summary
A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
- Type
- Chapter
- Information
- Improving Homeland Security Decisions , pp. 396 - 426Publisher: Cambridge University PressPrint publication year: 2017
References
Abbas, A. E. (2004). Entropy methods in decision analysis. PhD Thesis. Stanford University.Google Scholar
Abbas, A. E. (2009). Multiattribute utility copulas. Operations Research, 57(6), 1367–1383.CrossRefGoogle Scholar
Abbas, A. E. (2011). General decompositions of multiattribute utility functions. Journal of Multicriteria Decision Analysis, 17(1, 2), 37–59.CrossRefGoogle Scholar
Abbas, A. E. (2015, June). Perspectives on some widely used methods of multi-objective decision making. Proceedings of the IIE Annual Conference, Nashville, TN.Google Scholar
Abbas, A. E. (2017). Foundations of multiattribute utility. Cambridge: Cambridge University Press.Google Scholar
Abbas, A. E., & Aczel, J. (2010). The role of some functional equations in decision analysis. Decision Analysis, 7(2), 215–228.CrossRefGoogle Scholar
Abbas, A. E., & Bell, D. E. (2011). One-switch independence for multiattribute utility functions. Operations Research, 59(3), 764–771.Google Scholar
Abbas, A. E., & Bell, D. E. (2012). One-switch conditions for multiattribute utility functions. Operations Research, 60(5), 1199–1212.CrossRefGoogle Scholar
Abbas, A., Hazelrigg, G., & Al-Kindi, M. (2012). Bayesian inference for the demand of engineering products. ASME DTM International Design Engineering Technical Conferences and Computers and Information in Engineering Conference.CrossRefGoogle Scholar
Abbas, A. E., & Howard, R. A. (2005). Attribute dominance utility. Decision Analysis, 2(4), 185–206.Google Scholar
Abbas, A. E., & Matheson, J. E. (2009). Normative decision making with multiattribute performance targets. Journal of Multi-criteria Decision Analysis, 16(3–4), 67–78.CrossRefGoogle Scholar
Abbas, A. E., Matheson, J. E., & Bordley, R. F. (2009). Effective utility functions induced by organizational target-based incentives. Managerial and Decision Economics, 30(4), 235–251.Google Scholar
Arrow, K. J. (1965). The theory of risk aversion. Lecture 2 in Aspects of the Theory of Risk-Bearing. Yrjo Jahnssonin Saatio, Helsinki.Google Scholar
Bell, D. E. (1979). Multiattribute utility functions: Decompositions using interpolation. Management Science, 25, 744–753.Google Scholar
Debreu, G. (1960). Topological methods in cardinal utility theory. In Arrow, K., Karlin, S. & Suppes, P. (Eds.) Mathematical methods in the social sciences (pp. 16–26). Stanford, CA: Stanford University Press.Google Scholar
Dyer, J. (1990). Remarks on the analytic hierarchy process. Management Science, 36(3), 249–258.CrossRefGoogle Scholar
Farquhar, P. H. (1975). A fractional hypercube decomposition theorem for multiattribute utility functions. Operations Research, 23, 941–967.CrossRefGoogle Scholar
Fishburn, P. C. (1974). Von Neumann-Morgenstern utility functions on two attributes. Operations Research, 2, 35–45.Google Scholar
Fishburn, P. C. (1977). Approximations of two-attribute utility functions. Mathematics of Operations Research, 2, 30–44.CrossRefGoogle Scholar
Howard, R. A. (1966). Information value theory. IEEE Transactions on Systems Science and Cybernetics, 2(1), 22–26.CrossRefGoogle Scholar
Howard, R. A. (1980). On making life and death decisions. In R. A. Howard & J. E. Matheson (Eds.) The principles and applications of decision analysis, vol. II. Menlo Park, CA: Strategic Decisions Group.Google Scholar
Howard, R. A. (1992). In praise of the old time religion. In W. Edwards (Ed.) Utility theories: Measurements and applications. New York: Springer.Google Scholar
Howard, R. A., & Abbas, A. E. (2015). Foundations of decision analysis, 1st Edition. New York: Pearson.Google Scholar
Keeney, R. L., & Raiffa, H. (1976). Decisions with multiple objectives. New York: Wiley.Google Scholar
Lindley, D. (1982). Scoring rules and the inevitability of probability. International Statistical Review, 50(1), 1–11.CrossRefGoogle Scholar
Matheson, J. E., & Abbas, A. E. (2005). Utility transversality: A value-based approach. Journal of Multi-criteria Decision Analysis, 13(5–6), 229–238.Google Scholar
Matheson, J. E., & Howard, R. A. (1968). An introduction to decision analysis. In R. A. Howard and J. E. Matheson (Eds.), The principles and applications of decision analysis. Menlo Park, CA: Strategic Decisions Group.Google Scholar
Pratt, J. (1964). Risk aversion in the small and in the large. Econometrica, 32, 122–136.Google Scholar
Saaty, T. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48, 9–26.CrossRefGoogle Scholar
Savage, L. (1951). The theory of statistical decision, Journal of the American Statistical Association, 46, 55–67.CrossRefGoogle Scholar
Sun, Z., & Abbas, A. E. (2013). Bayesian updating on price elasticity of uncertain demand. IEEE International Systems Conference (SysCon), 222–228.Google Scholar
Traverso, M. G., & Abbas, A. E. (2009). Demand curve prediction via Bayesian probability assignment over a functional space. Winter Simulation Conference, 2971–2976.Google Scholar
von Neumann, J., & Morgenstern, J. (1947). Theory of games and economic behavior. Princeton, NJ: Princeton University Press.Google Scholar