Stochastic modeling and optimization : with applications in queues, finance, and supply chains随机塑造和优化
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作者： David D. Yao，Hanqin Zhang，Xun Yu Zhou著
出 版 社：
出版时间： 2007-1-1字数：版次： 1页数： 468印刷时间： 2007/01/01开本： 16开印次： 1纸张： 胶版纸I S B N ： 9780387955827包装： 精装编辑推荐
作者简介：David D. Yao (Columbia University) received his Ph.D. degree from the University of Toronto in 1983, and started his academic career at Columbia University, where he became a full professor in 1988, and a holder of Columbia's Thomas Alva Edison Chair in 1992. He has held a part-time appointment at IBM's T.J. Watson Research Center since 1990. His other academic appointments include Harvard (1986-88), Yale (1991/92), the Chinese University of Hong Kong, and Tsinghua University (Beijing).
He is an IEEE Fellow, and a recipient of numerous honors and awards, including the Guggenheim Fellowship (1991/92); the Presidential YoungInvestigator Award (1987-92) from the National Science Foundation (U.S.);the Franz Edelman Award (1999) from the Institute for Operations Research and Management Sciences; and from IBM Research, the Outstanding Technical Achievement Award (1999), Research Division Award (1996),and several Invention Achievement Awards.
Author/co-author of over 150 refereed publications, three books andfour edited volumes, he has served on the editorial board of several leading journals, including Discrete Event Dynamic Systems, IEEE Transactions on Automatic Control, Management Science, Operations Research, and Queueing Systems. A principal investigator of over two dozen research grants and contracts, he has done extensive research and consulting work in various aspects of semiconductor manufacturing, computer systems scheduling, Internet and web-server performance optimization, and supply chain management.He is a holder of foru U.S patents in manufacruing operations and supply chain logistics.
内容简介
This book covers the broad range of research in stochastic models and optimization. Applications covered include networks, financial engineering, production planning and supply chain management. Each contribution is aimed at graduate students working in operations research, probability, and statistics.
目录
1 Discrete-time Singularly Perturbed Markov Chains
G. Yin and Q. Zhang
1.1 Singularly Perturbed Markov Chains
1.1.1 Motivation
1.1.2 Preliminary
1.1.3 Singularly Perturbed Models
1.1.4 Motivating Examples
1.2 Asymptotic Expansions
1.3 Occupation Measures
1.4 Nonstationary Markov Chains and Applications
1.4.1 Asymptotic Properties for Smooth Transition Matrices
1.4.2 Bounded and Measurable Transition Matrices
1.4.3 Applications to Nearly Optimal Controls
1.5 Notes and Remarks
1.5.1 Notes on the Literature
1.5.2 Possible Future Research Topics
1.6 References
2 Nearly Optimal Controls of Markovian Systems
Q. Zhang, R.H. Liu, and G. Yin
2.1 Singularly Perturbed MDP
2.1.1 Irreducible MDP under Discounted Cost
2.1.2 Irreducible MDP under Long-Run Average Cost
2.1.3 MDP with General Transition Matrices
2.1.4 Historical Notes
2.2 Hybrid LQG Control
2.2.1 Aggregation and Approximation
2.2.2 Asymptotic Optimality
2.2.3 Hybrid LQG with General Transition Matrices
2.2.4 A Numerical Example
2.2.5 Historical Notes
2.3 Conclusions
2.4 References
3Stochastic Approximation, with Applications
Han-Fu Chen
9.2 A Stochastic LQ Control Approach
9.3 Efficient Frontier: Deterministic Market Parameters
9.4 Efficient Frontier: Random Adaptive Market Parameters
9.5 Efficient Frontier: Markov-Modulated Market Parameters
9.6 Efficient Frontier: No Short Selling
9.7 Mean-Variance Hedging
9.8 Notes
9.9 References
10 Variance Minimization in Stochastic Systems
Duan Li, Fucai Qian and Peilin Fu
10.1 Variance Minimization Problem
10.2 General Variance Minimization Problem
10.3 Variance Minimization in Dynamic Portfolio Selection
10.4 Variance Minimization in Dual Control
10.5 Notes
10.6 References
11 A Markov Chain Method for Pricing Contingent Claims
Jin-Chuan Duan, Genevieve Gauthier and Jean-Guy Simonato
11.1 The Markov Chain Pricing Method
11.2 The Black-Scholes (1973) Pricing Model
11.2.1 Choosing the Set of Asset Prices
11.2.2 Computing Transition Probabilities and Option Prices
11.2.3 An Illustrative Example
11.2.4 A Markov Chain Interpretation of Binomial Tree
11.2.5 Numerical Examples
11.3 The GARCH Pricing Model
11.3.1 Choosing the Set of Discrete Prices and Volatilities
11.3.2 Computing Transition Probabilities and Option Prices
11.3.3 Numerical Examples
11.4 Valuing Exotic Options
11.5 Appendix: The Conditional Expected Value of hT. and h2T
11.6 References
12 Stochastic Network Models and Optimization of a Hospital
System
Xiuli Chao, Liming Liu and Shaohui Zheng
12.1 A Multi-Site Service Network Model
12.2 Patient Flow Management
12.3 Capacity Design
12.4 Switching Costs and Quality of Service
12.5 Insights and Future Research Directions
12.6 Notes
12.7 References
13Optimal Airline Booking Control with Cancellations
Youyi Feng,Ping Lin and Baichun Xiao
14 Information Revision and Decision Making in Supply Chain Management
Houmin Yan and Hanqin Zhang
About the Contributors