Conditional Monte Carlo: Gradient Estimation and Optimization Applications
Conditional Monte Carlo: Gradient Estimation and Optimization Applications deals with various gradient estimation techniques of perturbation analysis based on the use of conditional expectation. The primary setting is discrete-event stochastic simulation. This book presents applications to queueing...
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| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Boston, MA
Springer US
1997
|
| Series: | The Springer International Series in Engineering and Computer Science, Discrete Event Dynamic Systems
392 |
| Subjects: | |
| Links: | https://doi.org/10.1007/978-1-4615-6293-1 https://doi.org/10.1007/978-1-4615-6293-1 |
| Summary: | Conditional Monte Carlo: Gradient Estimation and Optimization Applications deals with various gradient estimation techniques of perturbation analysis based on the use of conditional expectation. The primary setting is discrete-event stochastic simulation. This book presents applications to queueing and inventory, and to other diverse areas such as financial derivatives, pricing and statistical quality control. To researchers already in the area, this book offers a unified perspective and adequately summarizes the state of the art. To researchers new to the area, this book offers a more systematic and accessible means of understanding the techniques without having to scour through the immense literature and learn a new set of notation with each paper. To practitioners, this book provides a number of diverse application areas that makes the intuition accessible without having to fully commit to understanding all the theoretical niceties. In sum, the objectives of this monograph are two-fold: to bring together many of the interesting developments in perturbation analysis based on conditioning under a more unified framework, and to illustrate the diversity of applications to which these techniques can be applied. Conditional Monte Carlo: Gradient Estimation and Optimization Applications is suitable as a secondary text for graduate level courses on stochastic simulations, and as a reference for researchers and practitioners in industry |
| Physical Description: | 1 Online-Ressource (XV, 399 p) |
| ISBN: | 9781461562931 |
| DOI: | 10.1007/978-1-4615-6293-1 |
Staff View
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| series2 | The Springer International Series in Engineering and Computer Science, Discrete Event Dynamic Systems |
| spelling | Fu, Michael Verfasser aut Conditional Monte Carlo Gradient Estimation and Optimization Applications by Michael Fu, Jian-Qiang Hu Boston, MA Springer US 1997 1 Online-Ressource (XV, 399 p) txt rdacontent c rdamedia cr rdacarrier The Springer International Series in Engineering and Computer Science, Discrete Event Dynamic Systems 392 Conditional Monte Carlo: Gradient Estimation and Optimization Applications deals with various gradient estimation techniques of perturbation analysis based on the use of conditional expectation. The primary setting is discrete-event stochastic simulation. This book presents applications to queueing and inventory, and to other diverse areas such as financial derivatives, pricing and statistical quality control. To researchers already in the area, this book offers a unified perspective and adequately summarizes the state of the art. To researchers new to the area, this book offers a more systematic and accessible means of understanding the techniques without having to scour through the immense literature and learn a new set of notation with each paper. To practitioners, this book provides a number of diverse application areas that makes the intuition accessible without having to fully commit to understanding all the theoretical niceties. In sum, the objectives of this monograph are two-fold: to bring together many of the interesting developments in perturbation analysis based on conditioning under a more unified framework, and to illustrate the diversity of applications to which these techniques can be applied. Conditional Monte Carlo: Gradient Estimation and Optimization Applications is suitable as a secondary text for graduate level courses on stochastic simulations, and as a reference for researchers and practitioners in industry Computer Science Discrete Mathematics in Computer Science Probability Theory and Stochastic Processes Systems Theory, Control Calculus of Variations and Optimal Control; Optimization Computer science Computer science / Mathematics System theory Calculus of variations Probabilities Gradientenverfahren (DE-588)4157995-1 gnd rswk-swf Monte-Carlo-Simulation (DE-588)4240945-7 gnd rswk-swf Störungstheorie (DE-588)4128420-3 gnd rswk-swf Monte-Carlo-Simulation (DE-588)4240945-7 s Störungstheorie (DE-588)4128420-3 s Gradientenverfahren (DE-588)4157995-1 s 1\p DE-604 Hu, Jian-Qiang aut Erscheint auch als Druck-Ausgabe 9781461378891 https://doi.org/10.1007/978-1-4615-6293-1 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Fu, Michael Hu, Jian-Qiang Conditional Monte Carlo Gradient Estimation and Optimization Applications Computer Science Discrete Mathematics in Computer Science Probability Theory and Stochastic Processes Systems Theory, Control Calculus of Variations and Optimal Control; Optimization Computer science Computer science / Mathematics System theory Calculus of variations Probabilities Gradientenverfahren (DE-588)4157995-1 gnd Monte-Carlo-Simulation (DE-588)4240945-7 gnd Störungstheorie (DE-588)4128420-3 gnd |
| subject_GND | (DE-588)4157995-1 (DE-588)4240945-7 (DE-588)4128420-3 |
| title | Conditional Monte Carlo Gradient Estimation and Optimization Applications |
| title_auth | Conditional Monte Carlo Gradient Estimation and Optimization Applications |
| title_exact_search | Conditional Monte Carlo Gradient Estimation and Optimization Applications |
| title_full | Conditional Monte Carlo Gradient Estimation and Optimization Applications by Michael Fu, Jian-Qiang Hu |
| title_fullStr | Conditional Monte Carlo Gradient Estimation and Optimization Applications by Michael Fu, Jian-Qiang Hu |
| title_full_unstemmed | Conditional Monte Carlo Gradient Estimation and Optimization Applications by Michael Fu, Jian-Qiang Hu |
| title_short | Conditional Monte Carlo |
| title_sort | conditional monte carlo gradient estimation and optimization applications |
| title_sub | Gradient Estimation and Optimization Applications |
| topic | Computer Science Discrete Mathematics in Computer Science Probability Theory and Stochastic Processes Systems Theory, Control Calculus of Variations and Optimal Control; Optimization Computer science Computer science / Mathematics System theory Calculus of variations Probabilities Gradientenverfahren (DE-588)4157995-1 gnd Monte-Carlo-Simulation (DE-588)4240945-7 gnd Störungstheorie (DE-588)4128420-3 gnd |
| topic_facet | Computer Science Discrete Mathematics in Computer Science Probability Theory and Stochastic Processes Systems Theory, Control Calculus of Variations and Optimal Control; Optimization Computer science Computer science / Mathematics System theory Calculus of variations Probabilities Gradientenverfahren Monte-Carlo-Simulation Störungstheorie |
| url | https://doi.org/10.1007/978-1-4615-6293-1 |
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