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Título : Average—Cost Control of Stochastic Manufacturing Systems Tipo de documento: documento electrónico Autores: Sethi, Suresh P ; SpringerLink (Online service) ; Hanqin Zhang ; Qing Zhang Editorial: New York, NY : Springer New York Fecha de publicación: 2005 Colección: Stochastic Modelling and Applied Probability, ISSN 0172-4568 num. 54 Número de páginas: XVI, 324 p Il.: online resource ISBN/ISSN/DL: 978-0-387-27615-1 Idioma : Inglés (eng) Palabras clave: Business Leadership Production management Operations research Decision making Applied mathematics Engineering System theory Probabilities and Management Strategy/Leadership Applications of Mathematics Systems Theory, Control Probability Theory Stochastic Processes Operation Research/Decision Clasificación: 51 Matemáticas Resumen: This book is concerned with hierarchical control of manufacturing systems under uncertainty. It focuses on system performance measured in long-run average cost criteria, exploring the relationship between control problems with a discounted cost and that with a long-run average cost in connection with hierarchical control. A new theory is articulated that shows that hierarchical decision making in the context of a goal-seeking manufacturing system can lead to a near optimization of its objective. The approach in the book considers manufacturing systems in which events occur at different time scales. Nota de contenido: and Models of Manufacturing Systems -- Concept of Near—Optimal Control -- Models of Manufacturing Systems -- Optimal Control of Manufacturing Systems: Existence and Characterization -- Optimal Control of Parallel—Machine Systems -- Optimal Control of Dynamic Flowshops -- Optimal Controls of Dynamic Jobshops -- Risk-Sensitive Control -- Near—Optimal Controls -- Near—Optimal Control of Parallel—Machine Systems -- Near—Optimal Control of Dynamic Flowshops -- Near—Optimal Controls of Dynamic Jobshops -- Near—Optimal Risk—Sensitive Control -- Conclusions -- Further Extensions and Open Research Problems En línea: http://dx.doi.org/10.1007/0-387-27615-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35129 Average—Cost Control of Stochastic Manufacturing Systems [documento electrónico] / Sethi, Suresh P ; SpringerLink (Online service) ; Hanqin Zhang ; Qing Zhang . - New York, NY : Springer New York, 2005 . - XVI, 324 p : online resource. - (Stochastic Modelling and Applied Probability, ISSN 0172-4568; 54) .
ISBN : 978-0-387-27615-1
Idioma : Inglés (eng)
Palabras clave: Business Leadership Production management Operations research Decision making Applied mathematics Engineering System theory Probabilities and Management Strategy/Leadership Applications of Mathematics Systems Theory, Control Probability Theory Stochastic Processes Operation Research/Decision Clasificación: 51 Matemáticas Resumen: This book is concerned with hierarchical control of manufacturing systems under uncertainty. It focuses on system performance measured in long-run average cost criteria, exploring the relationship between control problems with a discounted cost and that with a long-run average cost in connection with hierarchical control. A new theory is articulated that shows that hierarchical decision making in the context of a goal-seeking manufacturing system can lead to a near optimization of its objective. The approach in the book considers manufacturing systems in which events occur at different time scales. Nota de contenido: and Models of Manufacturing Systems -- Concept of Near—Optimal Control -- Models of Manufacturing Systems -- Optimal Control of Manufacturing Systems: Existence and Characterization -- Optimal Control of Parallel—Machine Systems -- Optimal Control of Dynamic Flowshops -- Optimal Controls of Dynamic Jobshops -- Risk-Sensitive Control -- Near—Optimal Controls -- Near—Optimal Control of Parallel—Machine Systems -- Near—Optimal Control of Dynamic Flowshops -- Near—Optimal Controls of Dynamic Jobshops -- Near—Optimal Risk—Sensitive Control -- Conclusions -- Further Extensions and Open Research Problems En línea: http://dx.doi.org/10.1007/0-387-27615-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35129 Ejemplares
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Título : Continuous-Time Markov Chains and Applications : A Two-Time-Scale Approach Tipo de documento: documento electrónico Autores: G. George Yin ; SpringerLink (Online service) ; Qing Zhang Editorial: New York, NY : Springer New York Fecha de publicación: 2013 Otro editor: Imprint: Springer Colección: Stochastic Modelling and Applied Probability, ISSN 0172-4568 num. 37 Número de páginas: XXII, 430 p Il.: online resource ISBN/ISSN/DL: 978-1-4614-4346-9 Idioma : Inglés (eng) Palabras clave: Mathematics Calculus of variations Operations research Management science Probabilities Applied mathematics Engineering Probability Theory and Stochastic Processes Variations Optimal Control; Optimization Research, Science Appl.Mathematics/Computational Methods Clasificación: 51 Matemáticas Resumen: This book gives a systematic treatment of singularly perturbed systems that naturally arise in control and optimization, queueing networks, manufacturing systems, and financial engineering. It presents results on asymptotic expansions of solutions of Komogorov forward and backward equations, properties of functional occupation measures, exponential upper bounds, and functional limit results for Markov chains with weak and strong interactions. To bridge the gap between theory and applications, a large portion of the book is devoted to applications in controlled dynamic systems, production planning, and numerical methods for controlled Markovian systems with large-scale and complex structures in the real-world problems. This second edition has been updated throughout and includes two new chapters on asymptotic expansions of solutions for backward equations and hybrid LQG problems. The chapters on analytic and probabilistic properties of two-time-scale Markov chains have been almost completely rewritten and the notation has been streamlined and simplified. This book is written for applied mathematicians, engineers, operations researchers, and applied scientists. Selected material from the book can also be used for a one semester advanced graduate-level course in applied probability and stochastic processes Nota de contenido: Prologue and Preliminaries: Introduction and overview- Mathematical preliminaries -- Markovian models -- Two-Time-Scale Markov Chains: Asymptotic Expansions of Solutions for Forward Equations -- Occupation Measures: Asymptotic Properties and Ramification -- Asymptotic Expansions of Solutions for Backward Equations -- Applications:MDPs, Near-optimal Controls, Numerical Methods, and LQG with Switching: Markov Decision Problems -- Stochastic Control of Dynamical Systems -- Numerical Methods for Control and Optimization -- Hybrid LQG Problems -- References -- Index.- En línea: http://dx.doi.org/10.1007/978-1-4614-4346-9 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32219 Continuous-Time Markov Chains and Applications : A Two-Time-Scale Approach [documento electrónico] / G. George Yin ; SpringerLink (Online service) ; Qing Zhang . - New York, NY : Springer New York : Imprint: Springer, 2013 . - XXII, 430 p : online resource. - (Stochastic Modelling and Applied Probability, ISSN 0172-4568; 37) .
ISBN : 978-1-4614-4346-9
Idioma : Inglés (eng)
Palabras clave: Mathematics Calculus of variations Operations research Management science Probabilities Applied mathematics Engineering Probability Theory and Stochastic Processes Variations Optimal Control; Optimization Research, Science Appl.Mathematics/Computational Methods Clasificación: 51 Matemáticas Resumen: This book gives a systematic treatment of singularly perturbed systems that naturally arise in control and optimization, queueing networks, manufacturing systems, and financial engineering. It presents results on asymptotic expansions of solutions of Komogorov forward and backward equations, properties of functional occupation measures, exponential upper bounds, and functional limit results for Markov chains with weak and strong interactions. To bridge the gap between theory and applications, a large portion of the book is devoted to applications in controlled dynamic systems, production planning, and numerical methods for controlled Markovian systems with large-scale and complex structures in the real-world problems. This second edition has been updated throughout and includes two new chapters on asymptotic expansions of solutions for backward equations and hybrid LQG problems. The chapters on analytic and probabilistic properties of two-time-scale Markov chains have been almost completely rewritten and the notation has been streamlined and simplified. This book is written for applied mathematicians, engineers, operations researchers, and applied scientists. Selected material from the book can also be used for a one semester advanced graduate-level course in applied probability and stochastic processes Nota de contenido: Prologue and Preliminaries: Introduction and overview- Mathematical preliminaries -- Markovian models -- Two-Time-Scale Markov Chains: Asymptotic Expansions of Solutions for Forward Equations -- Occupation Measures: Asymptotic Properties and Ramification -- Asymptotic Expansions of Solutions for Backward Equations -- Applications:MDPs, Near-optimal Controls, Numerical Methods, and LQG with Switching: Markov Decision Problems -- Stochastic Control of Dynamical Systems -- Numerical Methods for Control and Optimization -- Hybrid LQG Problems -- References -- Index.- En línea: http://dx.doi.org/10.1007/978-1-4614-4346-9 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32219 Ejemplares
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Título : Controlled Markov Processes and Viscosity Solutions Tipo de documento: documento electrónico Autores: Wendell H. Fleming ; SpringerLink (Online service) ; H.M. Soner Editorial: New York, NY : Springer New York Fecha de publicación: 2006 Colección: Stochastic Modelling and Applied Probability, ISSN 0172-4568 num. 25 Número de páginas: XVII, 429 p Il.: online resource ISBN/ISSN/DL: 978-0-387-31071-8 Idioma : Inglés (eng) Palabras clave: Mathematics Operations research Decision making Economics, Mathematical System theory Probabilities Control engineering Robotics Mechatronics Probability Theory and Stochastic Processes Systems Theory, Control, Robotics, Operation Research/Decision Quantitative Finance Clasificación: 51 Matemáticas Resumen: This book is intended as an introduction to optimal stochastic control for continuous time Markov processes and to the theory of viscosity solutions. Stochastic control problems are treated using the dynamic programming approach. The authors approach stochastic control problems by the method of dynamic programming. The fundamental equation of dynamic programming is a nonlinear evolution equation for the value function. For controlled Markov diffusion processes, this becomes a nonlinear partial differential equation of second order, called a Hamilton-Jacobi-Bellman (HJB) equation. Typically, the value function is not smooth enough to satisfy the HJB equation in a classical sense. Viscosity solutions provide framework in which to study HJB equations, and to prove continuous dependence of solutions on problem data. The theory is illustrated by applications from engineering, management science, and financial economics. In this second edition, new material on applications to mathematical finance has been added. Concise introductions to risk-sensitive control theory, nonlinear H-infinity control and differential games are also included. Review of the earlier edition: "This book is highly recommended to anyone who wishes to learn the dinamic principle applied to optimal stochastic control for diffusion processes. Without any doubt, this is a fine book and most likely it is going to become a classic on the area... ." SIAM Review, 1994 Nota de contenido: Deterministic Optimal Control -- Viscosity Solutions -- Optimal Control of Markov Processes: Classical Solutions -- Controlled Markov Diffusions in ?n -- Viscosity Solutions: Second-Order Case -- Logarithmic Transformations and Risk Sensitivity -- Singular Perturbations -- Singular Stochastic Control -- Finite Difference Numerical Approximations -- Applications to Finance -- Differential Games En línea: http://dx.doi.org/10.1007/0-387-31071-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34778 Controlled Markov Processes and Viscosity Solutions [documento electrónico] / Wendell H. Fleming ; SpringerLink (Online service) ; H.M. Soner . - New York, NY : Springer New York, 2006 . - XVII, 429 p : online resource. - (Stochastic Modelling and Applied Probability, ISSN 0172-4568; 25) .
ISBN : 978-0-387-31071-8
Idioma : Inglés (eng)
Palabras clave: Mathematics Operations research Decision making Economics, Mathematical System theory Probabilities Control engineering Robotics Mechatronics Probability Theory and Stochastic Processes Systems Theory, Control, Robotics, Operation Research/Decision Quantitative Finance Clasificación: 51 Matemáticas Resumen: This book is intended as an introduction to optimal stochastic control for continuous time Markov processes and to the theory of viscosity solutions. Stochastic control problems are treated using the dynamic programming approach. The authors approach stochastic control problems by the method of dynamic programming. The fundamental equation of dynamic programming is a nonlinear evolution equation for the value function. For controlled Markov diffusion processes, this becomes a nonlinear partial differential equation of second order, called a Hamilton-Jacobi-Bellman (HJB) equation. Typically, the value function is not smooth enough to satisfy the HJB equation in a classical sense. Viscosity solutions provide framework in which to study HJB equations, and to prove continuous dependence of solutions on problem data. The theory is illustrated by applications from engineering, management science, and financial economics. In this second edition, new material on applications to mathematical finance has been added. Concise introductions to risk-sensitive control theory, nonlinear H-infinity control and differential games are also included. Review of the earlier edition: "This book is highly recommended to anyone who wishes to learn the dinamic principle applied to optimal stochastic control for diffusion processes. Without any doubt, this is a fine book and most likely it is going to become a classic on the area... ." SIAM Review, 1994 Nota de contenido: Deterministic Optimal Control -- Viscosity Solutions -- Optimal Control of Markov Processes: Classical Solutions -- Controlled Markov Diffusions in ?n -- Viscosity Solutions: Second-Order Case -- Logarithmic Transformations and Risk Sensitivity -- Singular Perturbations -- Singular Stochastic Control -- Finite Difference Numerical Approximations -- Applications to Finance -- Differential Games En línea: http://dx.doi.org/10.1007/0-387-31071-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34778 Ejemplares
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Título : Cycle Representations of Markov Processes Tipo de documento: documento electrónico Autores: Sophia L. Kalpazidou ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2006 Colección: Stochastic Modelling and Applied Probability, ISSN 0172-4568 num. 28 Número de páginas: XX, 304 p. 17 illus Il.: online resource ISBN/ISSN/DL: 978-0-387-36081-2 Idioma : Inglés (eng) Palabras clave: Mathematics Probabilities Probability Theory and Stochastic Processes Clasificación: 51 Matemáticas Nota de contenido: Fundamentals of the Cycle Representations of Markov Processes -- Directed Circuits -- Genesis of Markov Chains by Circuits: The Circuit Chains -- Cycle Representations of Recurrent Denumerable Markov Chains -- Circuit Representations of Finite Recurrent Markov Chains -- Continuous Parameter Circuit Processes with Finite State Space -- Spectral Theory of Circuit Processes -- Higher-Order Circuit Processes -- Cycloid Markov Processes -- Markov Processes on Banach Spaces on Cycles -- The Cycle Measures -- Wide-Ranging Interpretations of the Cycle Representations of Markov Processes -- Applications of the Cycle Representations -- Stochastic Properties in Terms of Circuits -- Lévy’s Theorem Concerning Positiveness of Transition Probabilities -- The Rotational Theory of Markov Processes En línea: http://dx.doi.org/10.1007/0-387-36081-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34826 Cycle Representations of Markov Processes [documento electrónico] / Sophia L. Kalpazidou ; SpringerLink (Online service) . - New York, NY : Springer New York, 2006 . - XX, 304 p. 17 illus : online resource. - (Stochastic Modelling and Applied Probability, ISSN 0172-4568; 28) .
ISBN : 978-0-387-36081-2
Idioma : Inglés (eng)
Palabras clave: Mathematics Probabilities Probability Theory and Stochastic Processes Clasificación: 51 Matemáticas Nota de contenido: Fundamentals of the Cycle Representations of Markov Processes -- Directed Circuits -- Genesis of Markov Chains by Circuits: The Circuit Chains -- Cycle Representations of Recurrent Denumerable Markov Chains -- Circuit Representations of Finite Recurrent Markov Chains -- Continuous Parameter Circuit Processes with Finite State Space -- Spectral Theory of Circuit Processes -- Higher-Order Circuit Processes -- Cycloid Markov Processes -- Markov Processes on Banach Spaces on Cycles -- The Cycle Measures -- Wide-Ranging Interpretations of the Cycle Representations of Markov Processes -- Applications of the Cycle Representations -- Stochastic Properties in Terms of Circuits -- Lévy’s Theorem Concerning Positiveness of Transition Probabilities -- The Rotational Theory of Markov Processes En línea: http://dx.doi.org/10.1007/0-387-36081-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34826 Ejemplares
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Título : Fundamentals of Stochastic Filtering Tipo de documento: documento electrónico Autores: Alan Bain ; SpringerLink (Online service) ; Dan Crisan Editorial: New York, NY : Springer New York Fecha de publicación: 2009 Otro editor: Imprint: Springer Colección: Stochastic Modelling and Applied Probability, ISSN 0172-4568 num. 60 Número de páginas: XIII, 390 p Il.: online resource ISBN/ISSN/DL: 978-0-387-76896-0 Idioma : Inglés (eng) Palabras clave: Mathematics Economics, Mathematical Numerical analysis Probabilities Control engineering Robotics Mechatronics Probability Theory and Stochastic Processes Control, Robotics, Analysis Quantitative Finance Clasificación: 51 Matemáticas Resumen: The objective of stochastic filtering is to determine the best estimate for the state of a stochastic dynamical system from partial observations. The solution of this problem in the linear case is the well known Kalman-Bucy filter which has found widespread practical application. The purpose of this book is to provide a rigorous mathematical treatment of the non-linear stochastic filtering problem using modern methods. Particular emphasis is placed on the theoretical analysis of numerical methods for the solution of the filtering problem via particle methods. The book should provide sufficient background to enable study of the recent literature. While no prior knowledge of stochastic filtering is required, readers are assumed to be familiar with measure theory, probability theory and the basics of stochastic processes. Most of the technical results that are required are stated and proved in the appendices. The book is intended as a reference for graduate students and researchers interested in the field. It is also suitable for use as a text for a graduate level course on stochastic filtering. Suitable exercises and solutions are included Nota de contenido: Filtering Theory -- The Stochastic Process ? -- The Filtering Equations -- Uniqueness of the Solution to the Zakai and the Kushner–Stratonovich Equations -- The Robust Representation Formula -- Finite-Dimensional Filters -- The Density of the Conditional Distribution of the Signal -- Numerical Algorithms -- Numerical Methods for Solving the Filtering Problem -- A Continuous Time Particle Filter -- Particle Filters in Discrete Time En línea: http://dx.doi.org/10.1007/978-0-387-76896-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33866 Fundamentals of Stochastic Filtering [documento electrónico] / Alan Bain ; SpringerLink (Online service) ; Dan Crisan . - New York, NY : Springer New York : Imprint: Springer, 2009 . - XIII, 390 p : online resource. - (Stochastic Modelling and Applied Probability, ISSN 0172-4568; 60) .
ISBN : 978-0-387-76896-0
Idioma : Inglés (eng)
Palabras clave: Mathematics Economics, Mathematical Numerical analysis Probabilities Control engineering Robotics Mechatronics Probability Theory and Stochastic Processes Control, Robotics, Analysis Quantitative Finance Clasificación: 51 Matemáticas Resumen: The objective of stochastic filtering is to determine the best estimate for the state of a stochastic dynamical system from partial observations. The solution of this problem in the linear case is the well known Kalman-Bucy filter which has found widespread practical application. The purpose of this book is to provide a rigorous mathematical treatment of the non-linear stochastic filtering problem using modern methods. Particular emphasis is placed on the theoretical analysis of numerical methods for the solution of the filtering problem via particle methods. The book should provide sufficient background to enable study of the recent literature. While no prior knowledge of stochastic filtering is required, readers are assumed to be familiar with measure theory, probability theory and the basics of stochastic processes. Most of the technical results that are required are stated and proved in the appendices. The book is intended as a reference for graduate students and researchers interested in the field. It is also suitable for use as a text for a graduate level course on stochastic filtering. Suitable exercises and solutions are included Nota de contenido: Filtering Theory -- The Stochastic Process ? -- The Filtering Equations -- Uniqueness of the Solution to the Zakai and the Kushner–Stratonovich Equations -- The Robust Representation Formula -- Finite-Dimensional Filters -- The Density of the Conditional Distribution of the Signal -- Numerical Algorithms -- Numerical Methods for Solving the Filtering Problem -- A Continuous Time Particle Filter -- Particle Filters in Discrete Time En línea: http://dx.doi.org/10.1007/978-0-387-76896-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33866 Ejemplares
Signatura Medio Ubicación Sub-localización Sección Estado ningún ejemplar PermalinkPermalinkStochastic Control of Hereditary Systems and Applications / SpringerLink (Online service) ; Mou-Hsiung Chang (2008)
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