Managing Safety of Heterogeneous Systems

Name: Managing Safety of Heterogeneous Systems | Decisions under Uncertainties and Risks
Brand: Springer
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Decisions under Uncertainties and Risks

Yuri Ermoliev Marek Makowski Kurt Marti(Herausgeber*in)

Springer (Verlag)

1. Auflage

Erschienen am 31. Januar 2012

XXIII, 378 Seiten

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Inhalt

Intro
Managing Safety of Heterogeneous Systems
Preface
Contents
Contributors
List of Figures
List of Tables
Robust Management of Heterogeneous Systems under Uncertainties
1 Context
2 Decisions Under Uncertainties
3 Illustrative Examples
4 Robust Decisions for Heterogeneous Systems
5 Heterogeneity and Vulnerability
5.1 Discounting
5.2 Stochastic Optimization Versus Scenario Optimization
6 Summary
References
Part I Decisions Under Systemic Risk and Uncertainties
Systemic Risk and Security Management
1 Introduction
2 Standard Risks
3 Catastrophic and Systemic Risks
3.1 Applicability of Mean Values, Systemic Risk
3.2 Extreme Events and Unknown Risks
4 Security Management, Principal Agent Problem
4.1 Game Theoretic Approach
4.2 Decision-Theoretic Approach
5 Systemic Security
5.1 Preventive Randomized Solutions
5.2 Defensive Resource Allocation
5.3 Systemic Failures and Damages
6 Security of Electricity Networks
7 Computational Methods
7.1 Adaptive Monte Carlo Optimization for Two-Stage STO Models
7.2 Uncertain Distributions
7.3 Generalized Moment Problem
7.4 Duality Relations and Stochastic Optimization
8 Concluding Remarks
References
Robust Decisions under Risk for Imprecise Probabilities
1 Introduction
2 Robust Solution Concept
3 Tail Mean and Related Robust Solution Concepts
4 Dual LP Models
5 Portfolio Optimization
6 Conclusions
References
Combining Second-Order Belief Distributions with Qualitative Statements in Decision Analysis
1 Introduction
2 Decision Trees
3 Belief Distributions
3.1 Constrained Belief Distributions
3.2 Marginal Constrained Belief Distributions
3.3 Belief Distribution Over Expected Utility
4 Simulation from Expected Utilities
4.1 Special Case of Uniform Distributions
5 Summary and Conclusions
References
An Econometric Model Based on the Maxmin Expected Utility Model: An Application to Earthquake Insurance
1 Introduction
2 Ambiguity and the Maxmin Expected Utility Model
3 Application: Earthquake Insurance in Japan
4 Survey Data
5 Model
5.1 Expected Utility Model
5.2 Maxmin Expected Utility Model
5.3 Specification of Subjective Probability Distributions
5.4 Specification of Utility Function
5.5 Estimation Method
6 Results
6.1 Estimation Results of Simple Models
6.2 Estimated Effects of Personal Characteristics
7 Policy Implications
8 Conclusions
References
Part II Modeling Uncertainties of Heterogeneous Systems
Modeling Technological Change Under Increasing Returns and Uncertainty
1 Introduction
2 Increasing Returns and Uncertainty
3 Myopic Evolutionary Processes
3.1 Behavioral Models, Urn's Scheme
3.2 Market Processes
3.3 Potential Urn's Schemes, ``Trial-and-Error" Experiments
4 Valuation of Technological Changes
4.1 Net Present Value Analysis, Discounting
4.2 Real Option, Top-Down and Bottom-Up Models
5 Systemic Valuations
6 Interdependencies and Endogenous Risks
6.1 Multiagent Framework Under Uncertainty
6.2 Induced Systemic Risks
6.3 Uncertainty and Increasing Returns
7 Decisions Under Uncertainty
7.1 Scenario Analysis, Pareto Optimality
7.2 Interval Uncertainty, Attainable Sets, Worst-Case Analysis
7.3 Weights
7.4 Probabilistic Degree of Belief, Fuzzy Sets
8 Probabilistic and Stochastic Models
8.1 Risk Measures
8.2 Two-Stage Model
9 Concluding Remarks
References
Stochastic Programming Perspectiveon the Agency Problems Under Uncertainty
1 Introduction
2 Deterministic Case and Importance of Uncertainty
3 Stochastic Programming Formulations of Agency Problems
3.1 Formulation of Agency Problems with Uncertain Parameters
3.2 Two-Stage Stochastic Programming Problem with Bilevel Structure
3.3 Imperfect Knowledge of the Principal About the Agent
3.3.1 Benchmarks
3.3.2 Monitoring
3.4 Licensing
4 Solution Approaches
5 Conclusions
Appendix: Algorithm for Solution of Example 8
References
Sustainable Agriculture, Food Security, and Socio-Economic Risks in Ukraine
1 Introduction
2 Structural Changes in Ukrainian Agricultural Sector
3 Analysis of Pathways Towards Sustainable Rural Area Development
4 Numerical Application
5 Concluding Remarks
References
Multiple-Criteria Decision Support Systemfor Siemianówka Reservoir under Uncertainties
1 Introduction
2 The Upper Narew Mathematical Model
3 Inflow Forecasts
4 Optimization Problem
5 Results
6 Conclusions
References
Part III Uncertainty and Optimization
A Deterministic Algorithm for Global Optimization
1 Introduction
2 Preliminaries
3 Lower Bounds
3.1 Lipschitzian Lower Bounds in a General Case
3.2 Lipschitzian Lower Bounds for Unconstrained Optimization
3.3 Computing Lipschitz Constants
4 Algorithm Details
4.1 Algorithm Overview
4.2 Optimality Testing
4.3 Feasibility Testing
4.4 Updating the Record
5 Implementation and Experimental Results
6 Related Works
7 Conclusions
References
Robust Optimization by Fuzzy Linear Programming
1 Introduction
2 Optimizing Approach
2.1 Statement of the Problem
2.2 Possibility and Necessity
2.3 Possible and Necessary Optimalities
2.4 Robust Soft-Optimal Solutions
3 Satisficing Approach
4 Concluding Remarks
References
Various Types of Objective Functions of Clustering for Uncertain Data
1 Introduction
2 FCM-Based Clustering with Tolerance
2.1 Basic Concept of Tolerance
2.2 Fuzzy c-Means
2.3 Fuzzy c-Means with Tolerance
2.3.1 Standard Model on L2-Norm
2.3.2 Entropy-Based Model on L2-Norm
2.3.3 Standard Model on L1-Norm
2.3.4 Entropy-Based Model on L1-Norm
3 FCM-Based Clustering Using Penalty-Vector Regularization
3.1 Basic Concept of Penalty-Vector Regularization
3.2 Fuzzy c-Means Using Penalty-Vector Regularization
3.2.1 Standard Model on L2-Norm
3.2.2 Entropy-Based Model on L2-Norm
3.2.3 Standard Model on L1-Norm
3.2.4 Entropy-Based Model on L1-Norm
4 Conclusion
References
Part IV Analysis and Optimization of Technical Systems Under Uncertainty
Stochastic Optimal Open-Loop Feedback Control of Dynamic Structural Systems under Stochastic Uncertainty
1 Dynamic Structural Systems Under Stochastic Uncertainty
1.1 Stochastic Optimal Structural Control: Active Control
1.2 Robust (Optimal) Open-Loop Feedback Control
1.3 Stochastic Optimal Open-Loop Feedback Control
2 Expected Total Cost Function
3 Open-Loop Control Problem on the Remaining Time Interval [tb,tf]
4 Stochastic Hamiltonian of (5a-d)
4.1 Expected Hamiltonian (with Respect to the Time Interval [tb,tf] and Information Atb)
4.2 H-Minimal Control on [tb,tf]
5 Canonical Hamiltonian System
6 Minimum Energy Control
6.1 Endpoint Control
6.1.1 Quadratic Control Costs
6.2 Endpoint Control with Different Cost Functions
6.3 Weighted Quadratic Terminal Costs
6.3.1 Quadratic Control Costs
7 Nonzero Costs for Displacements
7.1 Quadratic Control and Terminal Costs
8 Example
9 Conclusion
References
Modeling and Processing of Uncertainty in Civil Engineering by Means of Fuzzy Randomness
1 Introduction
2 Modeling Fuzzy Data
3 Processing Fuzzy Random Variables
3.1 Variant I
3.2 Variant II
4 Examples
4.1 Analysis of a Strengthened Hypar Shell Roof Structure
4.2 Safety Assessment of a Shoring Wall
5 Conclusion
References
Optimal Design and Sensitivity of Large Spatial Trusses Under Uncertainty
1 General Formulation of the Problem
1.1 Recourse Problem as LP
1.2 Substitute Problems
1.2.1 Expected Value Problem
1.2.2 Recourse Problem with Discretization
2 Numerical Example
2.1 Variation of the Number of Storeys
2.1.1 Expected Value Problem
2.1.2 Recourse Problem with Discretization
2.2 Variation of the Standard Deviation
2.3 Further Numerical Aspects
3 Conclusion
References
Part V Analysis and Optimization of Economic Systems Under Uncertainty
Sustainable Agriculture in China: Estimation and Reduction of Nitrogen Impacts
1 Introduction
2 The Model
3 Numerical Application: A Case Study of China
4 Concluding Remarks
Appendix 1: Production Allocation Algorithm
Appendix 2: Stochastic Model for Production Allocation
References
Evaluation of Portfolio of Financial and Insurance Instruments: Simulation of Uncertainty
1 Introduction
2 Catastrophe Bonds
3 Portfolio Construction
4 Cat-Bond Pricing
5 Numerical Experiments
6 Uncertainties Problem
7 Conclusions
References
Pricing Catastrophe Bonds under Safety Constraints
1 Introduction
2 Catastrophe Bond Pricing Model and Moral Hazard
2.1 Assumptions and Model Structure
2.2 Application to Typhoon Risk in China
2.3 Moral Hazard
3 Model with Moral Hazard Safety Constraints
3.1 Moral Hazard Constraint
3.2 Comparative Analysis of Results
4 Conclusions
References

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