Author | Yao, David D. author |
---|---|
Title | Stochastic Modeling and Optimization [electronic resource] : With Applications in Queues, Finance, and Supply Chains / by David D. Yao, Xun Yu Zhou, Hanqin Zhang |
Imprint | New York, NY : Springer New York : Imprint: Springer, 2003 |
Connect to | http://dx.doi.org/10.1007/978-0-387-21757-4 |
Descript | XI, 468 p. online resource |
1 Discrete-time Singularly Perturbed Markov Chains -- 1.1 Singularly Perturbed Markov Chains -- 1.2 Asymptotic Expansions -- 1.3 Occupation Measures -- 1.4 Nonstationary Markov Chains and Applications -- 1.5 Notes and Remarks -- 1.6 References -- 2 Nearly Optimal Controls of Markovian Systems -- 2.1 Singularly Perturbed MDP -- 2.2 Hybrid LQG Control -- 2.3 Conclusions -- 2.4 References -- 3 Stochastic Approximation, with Applications -- 3.1 SA Algorithms -- 3.2 General Convergence Theorems by TS Method -- 3.3 Convergence Theorems Under State-Independent Conditions -- 3.4 Applications -- 3.5 Notes -- 3.6 References -- 4 Performance Potential Based Optimization and MDPs -- 4.1 Sensitivity Analysis and Performance Potentials -- 4.2 Markov Decision Processes -- 4.3 Problems with Discounted Performance Criteria -- 4.4 Single Sample Path Based Implementations -- 4.5 Time Aggregation -- 4.6 Connections to Perturbation Analysis -- 4.7 Application Examples -- 4.8 Notes -- 4.9 References -- 5 An Interior-Point Approach to Multi-Stage Stochastic Programming -- 5.1 Two-Stage Stochastic Linear Programming -- 5.2 A Case Study -- 5.3 Multiple Stage Stochastic Programming -- 5.4 An Interior Point Method -- 5.5 Finding Search Directions -- 5.6 Model Diagnosis -- 5.7 Notes -- 5.8 References -- 6 A Brownian Model of Stochastic Processing Networks -- 6.1 Preliminaries -- 6.2 Stochastic Processing Network Model -- 6.3 Examples of Stochastic Processing Networks -- 6.4 Brownian Model for Stochastic Processing Network -- 6.5 Brownian Approximation via Strong Approximation -- 6.6 Notes -- 6.7 Appendix: Strong Approximation vs. Heavy Traffic Approximation -- 6.8 References -- 7 Stability of General Processing Networks -- 7.1 Motivating Simulations -- 7.2 Open Processing Networks -- 7.3 Network and Fluid Model Equations -- 7.4 Connection between Artificial and Standard Fluid Models -- 7.5 Examples of Stable Policies -- 7.6 Extensions -- 7.7 Appendix -- 7.8 Notes -- 7.9 References -- 8 Large Deviations, Long-Range Dependence, and Queues -- 8.1 Fractional Brownian Motion and a Related Filter -- 8.2 Moderate Deviations for Sample-Path Processes -- 8.3 MDP for the Filtered Process -- 8.4 Queueing Applications: The Workload Process -- 8.5 Verifying the Key Assumptions -- 8.6 Notes -- 8.7 References -- 9 Markowitzโs World in Continuous Time, and Beyond -- 9.1 The Mean-Variance Portfolio Selection Model -- 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 -- 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 -- 11.1 The Markov Chain Pricing Method -- 11.2 The Black-Scholes (1973) Pricing Model -- 11.3 The GARCH Pricing Model -- 11.4 Valuing Exotic Options -- 11.5 Appendix: The Conditional Expected Value of hT* and hT*2 -- 11.6 References -- 12 Stochastic Network Models and Optimization of a Hospital System -- 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 -- 13 Optimal Airline Booking Control with Cancellations -- 13.1 Preliminaries -- 13.2 The Minimum Acceptable Fare and Threshold Control -- 13.3 Extensions of the Basic Model -- 13.4 Numerical Experiments -- 13.5 Notes -- 13.6 References -- 14 Information Revision and Decision Making in Supply Chain Management -- 14.1 Industrial Examples -- 14.2 A Multi-Period, Two-Decision Model -- 14.3 A One-Period, Multi-Information Revision Model -- 14.4 Applications -- 14.5 Notes -- 14.6 References -- About the Contributors