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研究生:顏天保
研究生(外文):Yen, Tian-Bao
論文名稱:M/G/2/3的系統服務分配及機率的數值解
論文名稱(外文):The Numerical Solution of Density Function and Stationary Probability in Steady State of M/G/2/3
指導教授:彭南夫
指導教授(外文):Peng, Nan-Fu
口試委員:彭南夫鄭天澤王鴻龍洪慧念
口試委員(外文):Peng, Nan-FuWang, Hong-LongHong, Huei-Nian
口試日期:2017-06-26
學位類別:碩士
校院名稱:國立交通大學
系所名稱:統計學研究所
學門:數學及統計學門
學類:統計學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:30
中文關鍵詞:M/G/2/3M/G/C/K穩定機率已服務時間密度函數平衡方程式
外文關鍵詞:M/G/2/3M/G/C/KStationary probabilityThe density function of the time which has been servedBalance equations
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  • 被引用被引用:2
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  • 下載下載:5
  • 收藏至我的研究室書目清單書目收藏:0
藉由研究M/G/2/3服務系統的子密度分配(sub - density),
$f_1(s)$、$f_2(s,t)$、$f_3(s,t)$,分別代表系統在穩定狀態時系統有1、2、3人並且服務員已服務時間為s、(s,t)、(s,t)的密度函數,能較有效的求系統的穩定機率及其他特殊值。在這篇研究中我們找到M/M/2/3密度函數的解析解,和M/G/2/3的數值解以及近似解,其中近似解可表現為三個已知函數的線性組合,並且有不錯的效率和近似。之後我們試著將演算法推廣至M/G/2/K,並討論M/G/C/K計算上的可能方法。這篇論文的架構如下,第一章回顧相似的文獻並介紹這篇研究所使用的方法,第二章中探討M/M/2/3的情況,以矩陣運算的方式得到系統的密度函數及機率,第三章中探討M/G/2/3的情況,並列出數值演算法和近似演算法,第四章中列出實驗結果,第五章將演算法推廣至M/G/2/K並討論M/G/C/K的情況,第六章是結論。
By studying the sub-density of the M/G/2/3 queuing system,$f_1(s)$、$f_2(s,t)$、$f_3(s,t)$,which respectively stand for the
density function of the system in a steady state when the system has 1,2,3 people and they are has been serving for s, (s ,t), (s, t) unit of time, we can find the density function of the system and other special values (e.g.stationary probability). In this study, we find the analytical solution of the M/M/2/3, the numerical solution and the approximate solution of M/G/2/3 where the approximate solution can be expressed as the linear combination of several known functions and have good efficiency and approximation. We then try to extend the algorithm to M/G/2 /K and discuss possible approaches to M/G/C/K calculations. The structure of this paper is as follows. In the first chapter, we review the similar literature and introduce the method used in this study. In chapter 2, we discuss the situation of M/M/2/3, and solve the density function and the stationary probability. The third chapter to explore the M/G/2/3 situation, and lists the numerical algorithm and approximate algorithm. The fourth chapter lists the experimental results. The fifth chapter will be extended to M/G/2/K and discuss the case of M/G/C/K. In the end, the chapter sixth is the conclusion.
目錄
摘要...ii
Abstract...iii
誌謝...iv
目錄...v
圖目錄...vi
表目錄...vii
一、緒論...1
1.1 研究動機...1
1.2 文獻回顧...1
1.3 研究方法...2
二、M/M/2/3...6
2.1 平衡方程式...6
2.2 穩定機率理論解...7
三、M/G/2/3...10
3.1 平衡方程式...10
3.2 數值演算法...13
3.3 近似演算法...14
四、數值實驗...16
4.1 穩定機率實驗...16
4.2 服務分配實驗...17
五、M/G/C/K...20
5.1 M/G/2/K...20
5.2 M/G/C/K...21
六、結論...24
參考文獻...25
附錄一Stationary probability of M/M/2/3...27
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Sgouropoulos, N., Yao, Q., & Yastremiz, C. (2015). Matching a distribution by matching quantiles estimation. Journal of the American Statistical Association, 110(510), 742-759.

Tijms, H. C., Van Hoorn, M. H., & Federgruen, A. (1981). Approximations for the steady-state probabilities in the M/G/c queue. Advances in Applied Probability, 13(1), 186-206.

Xu, X., Wang, W., & Xu, S. (2008, October). Performance of a queuing model with Hyper-Erlang distribution service for wireless network nodes. In Wireless Communications, Networking and Mobile Computing, 2008. WiCOM'08. 4th International Conference on (pp. 1-4). IEEE.

Cossette, H., Landriault, D., Marceau, E., & Moutanabbir, K. Moment# Based Approximation with Mixed Erlang Distributions.

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Brandwajn, A., & Begin, T. (2014). Reduced complexity in M/Ph/c/N queues. Performance Evaluation, 78, 42-54.
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