| 書目名稱 | Stochastic Modeling and Optimization | | 副標題 | With Applications in | | 編輯 | David D. Yao,Xun Yu Zhou,Hanqin Zhang | | 視頻video | http://file.papertrans.cn/879/878003/878003.mp4 | | 圖書封面 |  | | 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 | | 關鍵詞 | 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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