Uncertainty Quantification in Variational Inequalities
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portes grátis
Uncertainty Quantification in Variational Inequalities
Theory, Numerics, and Applications
Jadamba, Baasansuren; Raciti, Fabio; Gwinner, Joachim; Khan, Akhtar A.
Taylor & Francis Ltd
12/2021
404
Dura
Inglês
9781138626324
15 a 20 dias
907
Descrição não disponível.
I. Variational Inequalities. 1. Preliminaries. 1.1. Elements of Functional Analysis. 1.2. Fundamentals of Measure Theory and Integration. 1.3. Essentials of Operator Theory. 1.4. An Overview of Convex Analysis and Optimization. 1.5. Comments and Bibliographical Notes. 2. Probability. 2.1. Probability Measure. 2.2. Conditional Probability and Independence. 2.3. Random Variables and Expectation. 2.4. Correlation, Independence, and Conditional Expectation. 2.5. Modes of Convergence of Random Variables. 2.6. Comments and Bibliographical Notes. 3. Projections on Convex Sets. 3.1. Projections on Convex Sets in Hilbert Spaces. 3.2. Projections on Convex Sets in Banach Spaces. 3.3. Comments and Bibliographical Notes. 4. Variational and Quasi-Variational Inequalities. 4.1. Illustrative Examples. 4.2. Linear Variational Inequalities. 4.3. Nonlinear Variational Inequalities. 4.4. Quasi Variational Inequalities. 4.5. Comments and Bibliographical Notes. 5. Numerical Methods for Variational and Quasi-Variational Inequalities. 5.1. Projection Methods. 5.2. Extragradient Methods. 5.3. Gap Functions and Descent Methods. 5.4. The Auxiliary Problem Principle. 5.5. Relaxation Method for Variational Inequalities. 5.6. Projection Methods for Quasi-Variational Inequalities. 5.7. Convergence of Recursive Sequences. 5.8. Comments and Bibliographical Notes. II. Uncertainty Quantification. Prologue on Uncertainty Quantification. 6. An Lp Approach for Variational Inequalities with Uncertain Data. 6.1. Linear Variational Inequalities with Random Data. 6.2. Nonlinear Variational Inequalities with Random Data. 6.3. Regularization of Variational Inequalities with Random Data. 6.4. Variational Inequalities with Mean-value Constraints. 6.5. Comments and Bibliographical Notes. 7. Expected Residual Minimization. 7.1. ERM for Linear Complementarity Problems. 7.2. ERM for Nonlinear Complementarity Problems. 7.3. ERM for Variational Inequalities. 7.4. Comments and Bibliographical Notes. 8. Stochastic Approximation Approach. 8.1. Stochastic Approximation. An Overview. 8.2. Gradient and Subgradient Stochastic Approximation. 8.3. Stochastic Approximation for Variational Inequalities. 8.4. Stochastic Iterative Regularization. 8.5. Stochastic Extragradient Method. 8.6. Incremental Projection Method. 8.7. Comments and Bibliographical Notes. III. Applications. 9. Uncertainty Quantification in Electric Power Markets. 9.1. Introduction. 9.2. The Model. 9.3. Complete Supply Chain Equilibrium Conditions. 9.4. Numerical Experiments. 9.5. Comments and Bibliographical Notes. 10. Uncertainty Quantification in Migration Models. 10.1. Introduction. 10.2. A Simple Model of Population Distributions. 10.3. A More Refined Model. 10.4. Numerical Examples. 10.5. Comments and Bibliographical Notes. 11. Uncertainty Quantification in Nash Equilibrium Problems. 11.1. Introduction. 11.2. Stochastic Nash Games and Variational Inequalities. 11.3. The Stochastic Oligopoly Model. 11.4. Uncertainty Quantification in Utility Functions. 11.5. Comments and Bibliographical Notes. 12. Uncertainty Quantification in Traffic Equilibrium Problems. 12.1 Introduction. 12.2. Traffic Equilibrium Problems via Variational Inequalities. 12.3. Uncertain Traffic Equilibrium Problems. 12.4. Computational Results. 12.5. A Comparative Study of Various Approaches. 12.6. Comments and Bibliographical Notes. Epilogue. Bibliography. Index.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Variational Inequality;stochastic analysis;Locally Convex Topological Vector Space;randomness;Variational Inequality Model;network models;Traffic Equilibrium Problem;economic models;Stochastic Variational Inequality;engineering models;Quasi-variational Inequalities;stochasticity;Extragradient Method;Nash Equilibrium Problems;Cumulative Distribution Function;Traffic Equilibrium Models;Feasible Path Flows;Variational Inequality Formulation;Hilbert Space;Banach Spaces;Reflexive Banach Space;Complementarity Problem;Sample Average Approximation Method;Stochastic Approximation Approach;Strongly Monotone;Strictly Monotone;Conditional Expectation;Maximal Monotone;Pointwise Constraints;Quasi-Monte Carlo Method;Nonlinear Complementarity Problems
I. Variational Inequalities. 1. Preliminaries. 1.1. Elements of Functional Analysis. 1.2. Fundamentals of Measure Theory and Integration. 1.3. Essentials of Operator Theory. 1.4. An Overview of Convex Analysis and Optimization. 1.5. Comments and Bibliographical Notes. 2. Probability. 2.1. Probability Measure. 2.2. Conditional Probability and Independence. 2.3. Random Variables and Expectation. 2.4. Correlation, Independence, and Conditional Expectation. 2.5. Modes of Convergence of Random Variables. 2.6. Comments and Bibliographical Notes. 3. Projections on Convex Sets. 3.1. Projections on Convex Sets in Hilbert Spaces. 3.2. Projections on Convex Sets in Banach Spaces. 3.3. Comments and Bibliographical Notes. 4. Variational and Quasi-Variational Inequalities. 4.1. Illustrative Examples. 4.2. Linear Variational Inequalities. 4.3. Nonlinear Variational Inequalities. 4.4. Quasi Variational Inequalities. 4.5. Comments and Bibliographical Notes. 5. Numerical Methods for Variational and Quasi-Variational Inequalities. 5.1. Projection Methods. 5.2. Extragradient Methods. 5.3. Gap Functions and Descent Methods. 5.4. The Auxiliary Problem Principle. 5.5. Relaxation Method for Variational Inequalities. 5.6. Projection Methods for Quasi-Variational Inequalities. 5.7. Convergence of Recursive Sequences. 5.8. Comments and Bibliographical Notes. II. Uncertainty Quantification. Prologue on Uncertainty Quantification. 6. An Lp Approach for Variational Inequalities with Uncertain Data. 6.1. Linear Variational Inequalities with Random Data. 6.2. Nonlinear Variational Inequalities with Random Data. 6.3. Regularization of Variational Inequalities with Random Data. 6.4. Variational Inequalities with Mean-value Constraints. 6.5. Comments and Bibliographical Notes. 7. Expected Residual Minimization. 7.1. ERM for Linear Complementarity Problems. 7.2. ERM for Nonlinear Complementarity Problems. 7.3. ERM for Variational Inequalities. 7.4. Comments and Bibliographical Notes. 8. Stochastic Approximation Approach. 8.1. Stochastic Approximation. An Overview. 8.2. Gradient and Subgradient Stochastic Approximation. 8.3. Stochastic Approximation for Variational Inequalities. 8.4. Stochastic Iterative Regularization. 8.5. Stochastic Extragradient Method. 8.6. Incremental Projection Method. 8.7. Comments and Bibliographical Notes. III. Applications. 9. Uncertainty Quantification in Electric Power Markets. 9.1. Introduction. 9.2. The Model. 9.3. Complete Supply Chain Equilibrium Conditions. 9.4. Numerical Experiments. 9.5. Comments and Bibliographical Notes. 10. Uncertainty Quantification in Migration Models. 10.1. Introduction. 10.2. A Simple Model of Population Distributions. 10.3. A More Refined Model. 10.4. Numerical Examples. 10.5. Comments and Bibliographical Notes. 11. Uncertainty Quantification in Nash Equilibrium Problems. 11.1. Introduction. 11.2. Stochastic Nash Games and Variational Inequalities. 11.3. The Stochastic Oligopoly Model. 11.4. Uncertainty Quantification in Utility Functions. 11.5. Comments and Bibliographical Notes. 12. Uncertainty Quantification in Traffic Equilibrium Problems. 12.1 Introduction. 12.2. Traffic Equilibrium Problems via Variational Inequalities. 12.3. Uncertain Traffic Equilibrium Problems. 12.4. Computational Results. 12.5. A Comparative Study of Various Approaches. 12.6. Comments and Bibliographical Notes. Epilogue. Bibliography. Index.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Variational Inequality;stochastic analysis;Locally Convex Topological Vector Space;randomness;Variational Inequality Model;network models;Traffic Equilibrium Problem;economic models;Stochastic Variational Inequality;engineering models;Quasi-variational Inequalities;stochasticity;Extragradient Method;Nash Equilibrium Problems;Cumulative Distribution Function;Traffic Equilibrium Models;Feasible Path Flows;Variational Inequality Formulation;Hilbert Space;Banach Spaces;Reflexive Banach Space;Complementarity Problem;Sample Average Approximation Method;Stochastic Approximation Approach;Strongly Monotone;Strictly Monotone;Conditional Expectation;Maximal Monotone;Pointwise Constraints;Quasi-Monte Carlo Method;Nonlinear Complementarity Problems
