Research Catalog

Title

Risk modeling, assessment, and management / Yacov Y. Haimes.

Author

Haimes, Yacov Y.

Publication

Hoboken, NJ : John Wiley & Sons, ©2009.

Items in the Library & Off-site

Details

Description

xxiii, 1009 pages : illustrations; 25 cm.

Summary

Integrates the art and science of risk analysis.; Clearly shows how to quantify risk and construct probability in conjunction with real-world decision-making problems, including a host of institutional, organizational, political, and cultural considerations.; Presents basic concepts as well as advanced material, avoiding higher mathematics whenever possible.; Incorporates numerous examples and case studies to illustrate the analytical methods under discussion.; An accompanying web site will offer 200 example problems and case studies.

Series Statement

Wiley series in systems engineering and management

Uniform Title

Wiley series in systems engineering and management.

Subject

• Technology > Risk assessment
• Technology > Risk assessment > Case studies
• Risk management
• Risk management > Case studies
• risk management
• Risk management
• Technology > Risk assessment
• Risikomanagement

Genre/Form

• Case studies
• Case studies.
• Études de cas.

Bibliography (note)

• Includes bibliographical references and index.

Contents

Part I. Fundamentals of Risk Modeling, Assessment, and Management -- 1. The Art and Science of Systems and Risk Analysis -- 1.1. Introduction -- 1.2. Systems Engineering -- 1.3. Risk Assessment and Management -- 1.4. Concept Road Map: The Farmer's Dilemma -- 1.5. Epilogue -- 2. The Role of Modeling in the Risk Analysis Process -- 2.1. Introduction -- 2.2. The Risk Assessment and Management Process -- 2.3. Information, Intelligence, and Models -- 2.4. The Building Blocks of Mathematical Models -- 2.5. The Farmer's Dilemma Revisited -- 2.6. Example Problems -- 3. Identifying Risk Through Hierarchical Holographic Modeling -- 3.1. Hierarchical Aspects -- 3.2. Hierarchical Overlapping Coordination -- 3.3. Hierarchical Holographic Modeling (HHM) -- 3.4. Hierarchical Holographic Modeling and the Theory of Scenario Structuring -- 3.5. Adaptive Multiplayer HHM (AMP-HHM) Game -- 3.6. Water Resource System -- 3.7. Sustainable Development -- 3.8. HHM in a System Acquisition Project -- 3.9. Software Acquisition -- 3.10. Hardening the Water Supply Infrastructure -- 3.11. Risk Assessment and Management for Support of Operations Other Than War -- 3.12. Automated Highway System -- 3.13. Food-Poisoning Scenarios -- 4. Decision Analysis -- 4.1. Introduction -- 4.2. Decision Rules Under Uncertainty -- 4.3. Decision Trees -- 4.4. Decision Matrix -- 4.5. The Fractile Method -- 4.6. Triangular Distribution -- 4.7. Influence Diagrams -- 4.8. Population Dynamics Models -- 4.9. Phantom System Models -- 4.10. Example Problems -- 5. Multiobjective Trade-Off Analysis -- 5.1. Introduction -- 5.2. Examples of Multiple Environmental Objectives -- 5.3. The Surrogate Worth Trade-off (SWT) Method -- 5.4. Characterizing a Proper Noninferior Solution -- 5.5. The Surrogate Worth Trade-off Method and the Utility -- 5.6. Example Problems -- 5.7. Summary -- 6. Defining Uncertainty and Sensitivity Analysis -- 6.1. Introduction -- 6.2. Sensitivity, Responsivity, Stability, and Irreversibility -- 6.3. Uncertainties Due to Errors in Modeling -- 6.4. Characterization of Modeling Errors -- 6.5. Uncertainty Taxonomy -- 6.6. The Uncertainty Sensitivity Index Method -- 6.7. Formulation of the Multiobjective Optimization Problem -- 6.8. A Robust Algorithm of the USIM -- 6.9. Integration of the USIM with Parameter Optimization at the Design Stage -- 6.10. Conclusions -- 7. Risk Filtering, Ranking, and Management -- 7.1. Introduction -- 7.2. Past Efforts in Risk Filtering and Ranking -- 7.3. Risk Filtering, Ranking, and Management A Methodological Framework -- 7.4. Case Study: An Operation Other Than War -- 7.5. Summary -- Part II. Advances in Risk Modeling, Assessment, and Management -- 8. Risk of Extreme Events and the Fallacy of Expected Value -- 8.1. Introduction -- 8.2. Risk of Extreme Events -- 8.3. The Fallacy of the Expected Value -- 8.4. The Partitioned Multiobjective Risk Method -- 8.5. General Formulation of the PMRM -- 8.6. Summary of the PMRM -- 8.7. Illustrative Example -- 8.8. Analysis of Dam Failure and Extreme Floods Through the PMRM -- 8.9. Example Problems -- 8.10. Summary -- 9. Multiobjective Decision-Tree Analysis -- 9.1. Introduction -- 9.2. Methodological Approach -- 9.3. Differences Between Single- and Multiple-Objective Decision Trees -- 9.4. Summary -- 9.5. Example Problems -- 10. Multiobjective Risk Impact Analysis Method -- 10.1. Introduction -- 10.2. Impact Analysis -- 10.3. The Multiobjective, Multistage Impact Analysis Method: An Overview -- 10.4. Combining the PMRM and the MMIAM -- 10.5. Relating Multiobjective Decision Trees to the Multiobjective Risk Impact Analysis Method -- 10.6. Example Problems -- 10.7. Epilogue -- 11. Statistics of Extremes: Extension of the PMRM -- 11.1. A Review of the Partitioned Multiobjective Risk Method -- 11.2. Statistics of Extremes -- 11.3. Incorporating the Statistics of Extremes into the PMRM -- 11.4. Sensitivity Analysis of the Approximation of f -- 11.5. Generalized Quantification of Risk of Extreme Events -- 11.6. Summary -- 11.7. Example Problems -- 12. Bayesian Analysis and the Prediction of Chemical Carcinogenicity -- 12.1. Background -- 12.2. Calculating Sensitivity and Specificity -- 12.3. Battery Selection -- 12.4. Determining the Performance (Predictivity and Selectivity) of the Test Battery -- 12.5. Trade-offs and Policy Analysis -- 13. Fault Trees -- 13.1. Introduction -- 13.2. Basic Fault-Tree Analysis -- 13.3. Reliability and Fault-Tree Analysis -- 13.4. Minimal Cut Sets -- 13.5. The Distribution Analyzer and Risk Evaluator Using Fault Trees -- 13.6. Extreme Events in Fault-Tree Analysis -- 13.7. An Example Problem Based on a Case Study -- 13.8. Failure Mode and Effects Analysis (FMEA) -- 13.9. Event Trees -- 13.10. Example Problems -- 14. Multiobjective Statistical Method -- 14.1. Introduction -- 14.2. Mathematical Formulation of the Interior Drainage Problem -- 14.3. Formulation of the Optimization Problem -- 14.4. The Multiobjective Statistical Method (MSM): Step-by-Step -- 14.5. The Surrogate Worth Trade-off (SWT) Method -- 14.6. Multiple Objectives -- 14.7. Applying the MSM -- 14.8. Example Problems -- 15. Principles and Guidelines for Project Risk Management -- 15.1. Introduction -- 15.2. Definitions and Principles of Project Risk Management -- 15.3. Project Risk Management Methods -- 15.4. Aircraft Development Example -- 15.5. Quantitative Risk Assessment and Management of Software Acquisition -- 15.6. Critical Factors That Affect Software Nontechnical Risk -- 15.7. Basis for Variances in Cost Estimation -- 15.8. Discrete Dynamic Modeling -- 15.9. Summary -- 16. Applying Risk Analysis to Space Missions -- 16.1. Introduction -- 16.2. Overview of Selected Space Missions -- 16.3. Risk Analysis Examples for Selected Space Missions -- 16.4. Hierarchical Holographic Modeling -- 16.5. Risk Filtering, Ranking, and Management -- 16.6. Epilogue -- 17. Risk Modeling, Assessment, and Management of Terrorism -- 17.1. Overview -- 17.2. On the Definition of Vulnerabilities in Measuring Risks to Infrastructures -- 17.3. Risk-Based Methodology for Scenario Tracking, Intelligence Gathering, and Analysis for Countering Terrorism -- 17.4. Homeland Security Preparedness: Balancing Protection with Resilience in Emergent Systems -- 17.5. Risk of Terrorism to Information Technology and to Critical Interdependent Infrastructures -- 18. Inoperability Input-Output Model and Its Derivatives for Interdependent Infrastructure Sectors -- 18.1. Overview -- 18.2. Background: The Original Leontief I/O Model -- 18.3. Inoperability Input-Output Model (IIM) -- 18.4. Regimes of Recovery -- 18.5. Supporting Databases for IIM Analysis -- 18.6. National and Regional Databases for IIM Analysis -- 18.7. Regional Input-Output Multiplier System (RIMS II) -- 18.8. Development of IIM and Its Derivatives -- 18.9. The Dynamic IIM -- 18.10. Practical Uses of IIM -- 18.11. Uncertainty IIM -- 18.12. Example Problems -- 18.13. Summary -- 19. Case Studies -- 19.1. A Risk-Based Input-Output Methodology for Measuring the Effects of the August 2003 Northeast Blackout -- 19.2. Systemic Valuation of Strategic Preparedness Through Applying the Inoperability Input-Output Model with Lessons Learned from Hurricane Katrina -- 19.3. Ex Post Analysis Using the IIM of the September 11, 2001 Attack on the US -- 19.4. Risk Modeling, Assessment, and Management of Lahar Flow Threat -- 19.5. The Statistics of Extreme Events and 6-Sigma Capability -- Appendix: Optimization Techniques -- Appendix A.1. Introduction to Modeling and Optimization -- Appendix A.2. Classical Unconstrained Optimization Problems -- Appendix A.3. Classical Equality Constraint Problem -- Appendix A.4. Newton-Raphson Method -- Appendix A.5. Linear Programming -- Appendix A.6. Dynamic Programming -- Appendix A.7. Generalized Nonlinear Programming -- Appendix A.8. Multiobjective Decision Trees -- Appendix A.9. Derivation of the Expected Value of a Log-normal Distribution -- Appendix A.10. Derivation of the Conditional Expected Value of a Log-normal Distribution -- Appendix A.11. Triangular Distribution: Unconditional and Conditional Expected Values -- Appendix A.12. Standard Normal Distribution Probability Table.

ISBN

• 9780470282373
• 0470282371

LCCN

2008026773

OCLC

• ocn232605676
• 232605676
• SCSB-9129426

Owning Institutions

Princeton University Library