Risk Modeling, Assessment, and Management

ISBN-13: 9781119017981 / Angielski / Twarda / 2015 / 720 str.

Yacov Y. Haimes

Opis

Presents systems-based theory, methodology, and applications in risk modeling, assessment, and management This book examines risk analysis, focusing on quantifying risk and constructing probabilities for real-world decision-making, including engineering, design, technology, institutions, organizations, and policy. The author presents fundamental concepts (hierarchical holographic modeling; state space; decision analysis; multi-objective trade-off analysis) as well as advanced material (extreme events and the partitioned multi-objective risk method; multi-objective decision trees; multi-objective risk impact analysis method; guiding principles in risk analysis); avoids higher mathematics whenever possible; and reinforces the material with examples and case studies. The book will be used in systems engineering, enterprise risk management, engineering management, industrial engineering, civil engineering, and operations research. The fourth edition of Risk Modeling, Assessment, and Management features:

• Expanded chapters on systems-based guiding principles for risk modeling, planning, assessment, management, and communication; modeling interdependent and interconnected complex systems of systems with phantom system models; and hierarchical holographic modeling
• An expanded appendix including a Bayesian analysis for the prediction of chemical carcinogenicity, and the Farmer's Dilemma formulated and solved using a deterministic linear model
• Updated case studies including a new case study on sequential Pareto-optimal decisions for emergent complex systems of systems
• A new companion website with over 200 solved exercises that feature risk analysis theories, methodologies, and application

Risk Modeling, Assessment, and Management, Fourth Edition, is written for both undergraduate and graduate students in systems engineering and systems management courses. The text also serves as a resource for academic, industry, and government professionals in the fields of homeland and cyber security, healthcare, physical infrastructure systems, engineering, business, and more.

Spis treści

Preface to the Fourth Edition ix

The Companion Website xv

Acknowledgments xvii

Part I. Fundamentals of Risk Modeling, Assessment, and Management 1

1 The Art and Science of Systems and Risk Analysis 3

1.1 Introduction / 3

1.2 Systems Engineering / 4

1.3 Risk Assessment and Management / 14

1.4 Concept Road Map / 26

1.5 Epilogue / 35

References / 35

2 The Role of Modeling in the Definition and Quantification of the Risk Function 41

2.1 Introduction / 41

2.2 The Risk Assessment and Management Process: Historical Perspectives / 43

2.3 Information, Intelligence, and Models / 45

2.4 The Building Blocks of Mathematical Models / 47

2.5 On the Complex Definition of Risk, Vulnerability, and Resilience: a Systems ]Based Approach / 51

2.6 On the Definition of Vulnerabilities in Measuring Risks to Systems / 56

2.7 On the Definition of Resilience in Measuring Risk to Systems / 57

2.8 On the Complex Quantification of Risk to Systems / 60

References / 65

3 Identifying Risk through Hierarchical Holographic Modeling and its Derivatives 69

3.1 Hierarchical Aspects / 69

3.2 Hierarchical Overlapping Coordination / 70

3.3 Hhm / 73

3.4 Hhm and the Theory of Scenario Structuring / 76

3.5 Adaptive Multiplayer Hhm Game / 79

3.6 Water Resources System / 80

3.7 Sustainable Development / 83

3.8 Hhm in a System Acquisition Project / 86

3.9 Software Acquisition / 90

3.10 Hardening the Water Supply Infrastructure / 94

3.11 Risk Assessment and Management for Support of Operations other than War / 98

3.12 Automated Highway System / 103

3.13 Food ]Poisoning Scenarios / 108

References / 113

4 Modeling and Decision Analysis 115

4.1 Introduction / 115

4.2 Decision Rules Under Uncertainty / 116

4.3 Decision Trees / 118

4.4 Decision Matrix / 122

4.5 The Fractile Method / 124

4.6 Triangular Distribution / 127

4.7 Influence Diagrams / 128

4.8 Population Dynamic Models / 132

4.9 PSM / 139

4.10 Example Problems / 144

References / 152

5 Multiobjective Trade ]off Analysis 155

5.1 Introduction / 155

5.2 Examples of Multiple Environmental Objectives / 157

5.3 The Surrogate Worth Trade ]off Method / 159

5.4 Characterizing a Proper Noninferior Solution / 166

5.5 The Swt Method and the Utility Function Approach / 168

5.6 Example Problems / 172

5.7 Summary / 177

References / 178

6 Defining Uncertainty and Sensitivity Analysis 179

6.1 Introduction / 179

6.2 Sensitivity, Responsivity, Stability, and Irreversibility / 180

6.3 Uncertainties Due to Errors in Modeling / 182

6.4 Characterization of Modeling Errors / 183

6.5 Uncertainty Taxonomy / 185

6.6 The Usim / 196

6.7 Formulation of the Multiobjective Optimization Problem / 199

6.8 A Robust Algorithm of the Usim / 204

6.9 Integration of the Usim with Parameter Optimization at the Design Stage / 207

6.10 Conclusions / 209

References / 209

7 Risk Filtering, Ranking, and Management 211

7.1 Introduction / 211

7.2 Past Efforts in Risk Filtering and Ranking / 212

7.3 Rfrm: A Methodological Framework / 213

7.4 Case Study: An Ootw / 220

7.5 Summary / 224

References / 224

Part II. Advances in Risk Modeling, Assessment, and Management 227

8 Risk of Extreme Events and the Fallacy of the Expected Value 229

8.1 Introduction / 229

8.2 Risk of Extreme Events / 230

8.3 The Fallacy of the Expected Value / 232

8.4 The Pmrm / 233

8.5 General Formulation of the Pmrm / 236

8.6 Summary of the Pmrm / 238

8.7 Illustrative Example / 239

8.8 Analysis of Dam Failure and Extreme Flood through the Pmrm / 240

8.9 Example Problems / 243

8.10 Summary / 257

References / 257

9 Multiobjective Decision ]tree Analysis 259

9.1 Introduction / 259

9.2 Methodological Approach / 261

9.3 Differences between Sodt and Modt / 279

9.4 Summary / 281

9.5 Example Problems / 282

References / 293

10 Multiobjective Risk Impact Analysis Method 295

10.1 Introduction / 295

10.2 Impact Analysis / 296

10.3 The Multiobjective, Multistage Impact Analysis Method: An Overview / 297

10.4 Combining the Pmrm and the Mmiam / 298

10.5 Relating Multiobjective Decision Trees to the Mriam / 304

10.6 Example Problems / 313

10.7 Epilogue / 325

References / 326

11 Statistics of Extremes: Extension of the PMRM 329

11.1 A Review of the Partitioned Multiobjective Risk Method / 329

11.2 Statistics of Extremes / 333

11.3 Incorporating the Statistics of Extremes into the Pmrm / 338

11.4 Sensitivity Analysis of the Approximation of f4(·) / 344

11.5 Generalized Quantification of Risk of Extreme Events / 350

11.6 Summary / 356

11.7 Example Problems / 357

References / 368

12 Systems ]Based Guiding Principles for Risk Modeling, Planning, Assessment, Management, and Communication 371

12.1 Introduction / 371

12.2 The Journey: The Guiding Principles in the Broader Context of the Emerging Next Generation Developed by the Federal Aviation Administration / 372

References / 387

13 Fault Trees 389

13.1 Introduction / 389

13.2 Basic Fault–Tree Analysis / 391

13.3 Reliability and Fault–Tree Analysis / 392

13.4 Minimal Cut Sets / 397

13.5 The DARE Using Fault Trees / 400

13.6 Extreme Events in Fault Tree Analysis / 403

13.7 An Example Problem Based on a Case Study / 405

13.8 Failure Mode and Effects Analysis and Failure Mode, Effects, and Criticality Analysis / 409

13.9 Event Trees / 411

13.10 Example Problems / 414

References / 420

14 Multiobjective Statistical Method 423

14.1 Introduction / 423

14.2 Mathematical Formulation of the Interior Drainage Problem / 424

14.3 Formulation of the Optimization Problem / 424

14.4 The Msm: Step–by–Step / 425

14.5 The Swt Method / 427

14.6 Multiple Objectives / 428

14.7 Applying the Msm / 429

14.8 Example Problems / 432

References / 438

15 Principles and Guidelines for Project Risk Management 439

15.1 Introduction / 439

15.2 Definitions and Principles of Project Risk Management / 440

15.3 Project Risk Management Methods / 443

15.4 Aircraft Development Example / 450

15.5 Quantitative Risk Assessment and Management of Software Acquisition / 454

15.6 Critical Factors That Affect Software Nontechnical Risk / 458

15.7 Basis for Variances in Cost Estimation / 460

15.8 Discrete Dynamic Modeling / 461

15.9 Summary / 469

References / 469

16 Modeling Complex Systems of Systems with Phantom System Models 473

16.1 Introduction / 473

16.2 What Have We Learned from Other Contributors? / 474

16.3 The Centrality of the States of the System in Modeling and in Risk Analysis / 476

16.4 The Centrality of Time in Modeling Multidimensional Risk, Uncertainty, and Benefits / 477

16.5 Extension of Hhm to Psm / 478

16.6 Psm and Meta–modeling / 480

16.7 Psm Laboratory / 486

16.8 Summary / 488

References / 489

17 Adaptive Two ]Player Hierarchical Holographic Modeling Game for Counterterrorism Intelligence Analysis 493

17.1 Introduction / 493

17.2 Bayes Theorem / 494

17.3 Modeling the Multiple Perspectives of Complex Systems / 495

17.4 Adaptive Two ]Player Hhm Game: Terrorist Networks versus Homeland Protection / 499

17.5 The Building Blocks of Mathematical Models and the Centrality of State Variables in Intelligence Analysis / 502

17.6 Hierarchical Adaptive Two ]Player Hhm Game / 504

17.7 Collaborative Computing Support for Adaptive Two ]Player Hhm Games / 505

17.8 Summary / 507

References / 508

18 Inoperability Input Output Model and Its Derivatives for Interdependent Infrastructure Sectors 511

18.1 Overview / 511

18.2 Background: The Original Leontief Input Output Model / 512

18.3 Inoperability Input Output Model / 513

18.4 Regimes of Recovery / 516

18.5 Supporting Databases for Iim Analysis / 517

18.6 National and Regional Databases for Iim Analysis / 518

18.7 Rims Ii / 522

18.8 Development of the Iim and its Extensions / 523

18.9 The Dynamic Iim / 527

18.10 Practical Uses of the Iim / 530

18.11 Uncertainty Iim / 533

18.12 Example Problems / 536

18.13 Summary / 539

References / 540

19 Case Studies 543

19.1 A Risk ]Based Input Output Methodology for Measuring the Effects of the August 2003 Northeast Blackout / 543

19.2 Systemic Valuation of Strategic Preparedness Through Applying the Iim with Lessons Learned from Hurricane Katrina / 558

19.3 Ex Post Analysis Using the Iim of the September 11, 2001, Attack on the United States / 569

19.4 Risk Modeling, Assessment, and Management of Lahar Flow Threat / 575

19.5 The Statistics of Extreme Events and 6 ]Sigma Capability / 587

19.6 Sequential Pareto ]Optimal Decisions Made During Emergent Complex Systems of Systems: An Application to the Faa Nextgen / 593

References / 612

Appendix: Optimization Techniques 617

A.1 Introduction to Modeling and Optimization / 617

A.2 Bayesian Analysis and the Prediction of Chemical Carcinogenicity / 655

A.3 The Farmer s Dilemma: Linear Model and Duality / 657

A.4 Standard Normal Probability Table / 664

References / 665

Author Index 667

Subject Index 673

Blurb

Examines the multidisciplinary applications, problems, and case histories in risk modeling, assessment, and management

This book examines risk analysis, focusing on quantifying risk and constructing probability in conjunction with real–world decision–making problems, including institutional, organizational, and political considerations. The author presents basic concepts (hierarchical holographic modeling; decision analysis; multi–objective trade–off analysis) as well as advanced material (extreme events and the partitioned multi–objective risk method; multi–objective decision–tree analysis; multi–objective risk impact analysis method); avoids higher mathematics whenever possible; and reinforces the material with examples and case studies.

The fourth edition of Risk Modeling, Assessment, and Management features:

• Expanded chapters covering systems–based guiding principles for risk modeling, planning, assessment, management, and communication; modeling complex systems of systems with phantom system models; and hierarchical holographic modeling
• An expanded appendix including the Bayesian analysis for the prediction of chemical carcinogenicity, and the Farmer s Dilemma formulated and solved using a deterministic linear model
• Updated case studies including a new case study on sequential Pareto–optimal decisions made during emergent complex systems of systems
• A new companion website with over 200 solved exercises and problems that feature risk analysis theories, methodologies, and applications

Risk Modeling, Assessment, and Management, Fourth Edition, is written for both undergraduate and graduate students in systems engineering and systems management courses. The text also serves as a resource for academic, industry, and government professionals in the fields of homeland and cyber security, healthcare, physical infrastructure systems, engineering, business, and more.

Yacov Y. Haimes, PhD., is the Lawrence R. Quarles Professor at the School of Engineering and Applied Science, University of Virginia, Charlottesville, and is a member of the Systems and Information Engineering faculty. He is the Founding Director (1987) of the university–wide Center for Risk Management of Engineering Systems. On the faculty of Case Western Reserve University, Cleveland, for 17 years, he was the Chair of the Systems Engineering Department, and Director of the Center for Large–Scale Systems and Policy Analysis.