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研究生: 顏源亨
Yen, Yuan Heng
論文名稱: 以矩陣分解法計算特別階段形機率分配並有多人服務之排隊模型
A phase-type queueing model with multiple servers by matrix decomposition approaches
指導教授: 陸行
Luh, Hsing
學位類別: 碩士
Master
系所名稱: 理學院 - 應用數學系數學教學碩士在職專班
論文出版年: 2011
畢業學年度: 99
語文別: 英文
論文頁數: 69
中文關鍵詞: 階段形機率分配多重服務器穩定狀態機率
外文關鍵詞: Phase-type distribution, multiple servers, stationary probability
相關次數: 點閱:99下載:23
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  • 穩定狀態機率是讓我們了解各種排隊網路性能的基礎。在擬生死過程(Quasi-Birth-and-Death) Phase-type 分配中求得穩定狀態機率,通常是依賴排隊網路的結構。在這篇論文中,我們提出了一種計算方法-LU分解,可以求得在排隊網路中有多台服務器的穩定狀態機率。此計算方法提供了一種通用的方法,使得複雜的大矩陣變成小矩陣,並減低計算的複雜性。當需要計算一個複雜的大矩陣,這個成果變得更加重要。文末,我們提到了離開時間間隔,並用兩種方法 (Matlab 和 Promodel) 去計算期望值和變異數,我們發現兩種方法算出的數據相近,接著計算離開顧客的時間間隔相關係數。最後,我們提供數值實驗以計算不同服務器個數產生的離去過程和相關係數,用來說明我們的方法。


    Stationary probabilities are fundamental in response to various measures of performance in queueing networks. Solving stationary probabilities in Quasi-Birth-and-Death(QBD) with phase-type distribution normally are dependent on the structure of the queueing network. In this thesis, a new computing scheme is developed for attaining stationary probabilities in queueing networks with multiple servers. This scheme provides a general approach of consindering the
    complexity of computing algorithm. The result becomes more
    significant when a large matrix is involved in computation. After determining the stationary probability, we study the departure process and the moments of inter-departure times. We can obtain the moment of inter-departure times. We compute the moments of inter-departure times and the variance by applying two numerical methods (Matlab and Promodel). The lag-k correlation of inter-departure times is also introduced in the thesis. The proposed approach is proved theoretically and verifieded with illustrative examples.

    1 Introdution 1
    2 Problem Definitions 4
    2.1 Markovian arrival process with phase-type
    distributions 4
    2.2 A Phase-type queueing model 7
    3 Matrix-Geometric Solutions 12
    3.1 State balance equations 12
    3.2 An algorithm for matrix decomposition 14
    4 Inter-departure times 23
    4.1 Departure process 23
    4.2 Moments of inter-departure times 25
    4.3 Lag correlations between successive departures 25
    5 Numerical Examples 27
    5.1 Queueing models with two servers 27
    5.2 Queueing models with three servers 37
    5.3 Queueing models with more than twenty servers 46
    5.4 Numerical experiments with more than forty servers 55
    6 Conclusion 59

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