Stochastic Modeling and Optimization [electronic resource] : With Applications in Queues, Finance, and Supply Chains /

The objective of this volume is to highlight through a collection of chap­ ters some of the recent research works in applied prob ability, specifically stochastic modeling and optimization. The volume is organized loosely into four parts. The first part is a col­ lection of several basic methodologies: singularly perturbed Markov chains (Chapter 1), and related applications in stochastic optimal control (Chapter 2); stochastic approximation, emphasizing convergence properties (Chapter 3); a performance-potential based approach to Markov decision program­ ming (Chapter 4); and interior-point techniques (homogeneous self-dual embedding and central path following) applied to stochastic programming (Chapter 5). The three chapters in the second part are concerned with queueing the­ ory. Chapters 6 and 7 both study processing networks - a general dass of queueing networks - focusing, respectively, on limit theorems in the form of strong approximation, and the issue of stability via connections to re­ lated fluid models. The subject of Chapter 8 is performance asymptotics via large deviations theory, when the input process to a queueing system exhibits long-range dependence, modeled as fractional Brownian motion.

Bibliographic Details

Main Authors:	Yao, David D. author., Zhou, Xun Yu. author., Zhang, Hanqin. author., SpringerLink (Online service)
Format:	Texto biblioteca
Language:	eng
Published:	New York, NY : Springer New York : Imprint: Springer, 2003
Subjects:	Mathematics., Operations research., Decision making., Economics, Mathematical., Management science., Probabilities., Operations Research, Management Science., Operation Research/Decision Theory., Quantitative Finance., Probability Theory and Stochastic Processes.,
Online Access:	http://dx.doi.org/10.1007/978-0-387-21757-4
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