| 书目名称 | Stochastic Modeling and Optimization | | 副标题 | With Applications in | | 编辑 | David D. Yao,Xun Yu Zhou,Hanqin Zhang | | 视频video | | | 图书封面 |  | | 描述 | 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 fr | | 出版日期 | Book 2003 | | 关键词 | Markov Chains; Markov chain; Rang; Stochastic Approximation; Stochastic Programming; Supply Chains; decisi | | 版次 | 1 | | doi | https://doi.org/10.1007/978-0-387-21757-4 | | isbn_softcover | 978-1-4419-3065-1 | | isbn_ebook | 978-0-387-21757-4 | | copyright | Springer Science+Business Media New York 2003 |
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发表于 2025-3-21 16:21:57
