JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2023, Vol. 58 ›› Issue (8): 104-110, 117.doi: 10.6040/j.issn.1671-9352.0.2021.786

Previous Articles     Next Articles

MPEWMA chart for detecting tandem queuing network

Qi GAO(),Hongshuai DAI,Yanhua WU*()   

  1. School of Statistics and Mathmatics, Shandong University of Finance and Economics, Jinan 250014, Shandong, China
  • Received:2021-11-28 Online:2023-08-20 Published:2023-07-28
  • Contact: Yanhua WU E-mail:1456283672@qq.com;wuyhup@126.com

Abstract:

We constructed a multivariate Poisson exponential weighted moving average (MPEWMA) chart, which can detect a series queuing network with intermediate inputs. The MPEWMA chart can be used to monitor and control multiple nodes in the system simultaneously. We detect the change points of the external arrival rate λiby the MPEWMA chart, segment the process according to the change points, and estimate the segmented parameters using the MLE method when each segment meets the stationarity of each segment. Under the constraint of the lowest cost, the estimated value of the arrival rate γi is calculated from external inputs λi, and the service process is optimized in a timely manner based on changes in the arrival rate. The service rate is adjusted reasonably to reduce customer waiting time. The random simulation results indicate that when the customer's arrival rate changes, the MPEWMA chart can timely detect changes in external arrival rate λi and issue alerts, playing an important role in the smooth operation of the queuing system.

Key words: tandem queuing network, MPEWMA chart, change point detection, system optimization

CLC Number: 

  • O211.9

Fig.1

Tandem queuing network with intermediate input"

Fig.2

Two-nodes tandem queuing network with intermediate input"

Table 1

The performance of ARL1 and δ in different shifts"

位移 [0,0] [0,1] [1,1] [0,2] [2,1] [2,2] [1,3] [2,3] [3,3] [3,4] [4,4]
δ 0 0.41 0.65 0.75 0.98 1.17 1.17 1.39 1.62 1.81 2.01
r=0.05 H=7.52 200.12 33.02 17.85 14.27 10.23 8.22 8.16 6.62 5.46 4.75 4.15
r=0.1 H=8.77 199.94 36.54 17.65 13.78 9.21 7.19 7.12 5.61 4.50 3.87 3.33
r=0.2 H=9.87 198.423 46.29 20.69 15.68 9.57 6.96 6.92 5.17 3.97 3.29 2.76

Fig.3

Relations between ARL1 and δ"

Fig.4

Detection of change-point in the model"

Table 2

The estimated values of λ in different stages"

λ1i λi2
节点1 3.044 2.923
节点2 5.238 5.964

Table 3

The results of system optimization"

最优服务率μ* 平均等待时间WSE 最优成本z
γ21=5.24 9.28 0.139 105.24
γ22=11.20 19.88 0.065 211.66

Fig.5

Manufacture of products model"

Fig.6

Detection of change-point in the model"

Table 4

The results of system optimization"

最优服务率μ* 平均等待时间EWs 最优成本z
γ21=15.39 27.96 0.044 875.42
γ21=17.02 30.92 0.039 964.25
1 KAYA Y B. Statistical monitoring of queuing networks[D]. Tampa: University of South Florida, 2018.
2 CHEN N , ZHOU S Y . CUSUM statistical monitoring of M/M/1 queues and extensions[J]. Technometrics, 2015, 57 (2): 245- 256.
doi: 10.1080/00401706.2014.923787
3 BHAT U N , RAO S S . A statistical technique for the control of traffic intensity in the queuing systems M/G/1 and GI/M/1[J]. Operations Research, 1972, 20 (5): 955- 966.
doi: 10.1287/opre.20.5.955
4 CHEN N , YUAN Y , ZHOU S Y . Performance analysis of queue length monitoring of M/G/1 systems[J]. Naval Research Logistics (NRL), 2011, 58 (8): 782- 794.
doi: 10.1002/nav.20483
5 WARDELL D G , MOSKOWITZ H , PLANTE R D . Control charts in the presence of data correlation[J]. Management Science, 1992, 38 (8): 1084- 1105.
doi: 10.1287/mnsc.38.8.1084
6 QI D Q , LI Z H , ZI X M , et al. Weighted likelihood ratio chart for statistical monitoring of queueing systems[J]. Quality Technology & Quantitative Management, 2017, 14 (1): 19- 30.
7 米红娟. 医院门诊排队网络分析[J]. 西北师范大学学报(自然科学版), 1998, 34 (2): 25- 31.
MI Hongjuan . Analysis on queueing network of hospital outpatient service[J]. Journal of Northwest Normal University (Natural Science), 1998, 34 (2): 25- 31.
8 常诚. 广义Jackson网络最优权重下的最优资源配置[D]. 南京: 南京大学, 2016.
CHANG Cheng. Optimal resource allocation under the best station weights in generalized Jackson network[D]. Nanjing: Nanjing University, 2016.
9 WEIN L M . Capacity allocation in generalized Jackson networks[J]. Operations Research Letters, 1989, 8 (3): 143- 146.
doi: 10.1016/0167-6377(89)90040-0
10 MAO X C , WU Z G . The optimizing of the passenger throughput at an airport security checkpoint[J]. Open Journal of Applied Sciences, 2017, 7 (9): 485- 501.
doi: 10.4236/ojapps.2017.79035
11 AZARON A , FATEMI GHOMI S M T . Optimal control of service rates and arrivals in Jackson networks[J]. European Journal of Operational Research, 2003, 147 (1): 17- 31.
doi: 10.1016/S0377-2217(02)00177-7
12 YAO D D, SCHECHNER Z. Decentralized control of service rates in a closed Jackson network[C]//26th IEEE Conference on Decision and Control. Los Argeles: IEEE, 2007: 1487-1490.
13 席少辉. 基于排队网络模型的大型制造系统资源配置优化研究[D]. 广州: 广东工业大学, 2019.
XI Shaohui. Research on resource allocation optimization of large-scale manufacturing system based on queuing network model[D]. Guangzhou: Guangdong University of Technology, 2019.
14 王兆军, 邹长亮, 李忠华. 统计质量控制图理论与方法[M]. 北京: 科学出版社, 2013.
WANG Zhaojun , ZOU Changliang , LI Zhonghua . Statistical quality control chart theory and methods[M]. Beijing: Science Press, 2013.
15 BERSIMIS S , PSARAKIS S , PANARETOS J . Multivariate statistical process control charts: an overview[J]. Quality and Reliability Engineering International, 2007, 23 (5): 517- 543.
doi: 10.1002/qre.829
16 HAN S W , TSUI K L , ARIYAJUNYA B , et al. A comparison of CUSUM, EWMA, and temporal scan statistics for detection of increases in Poisson rates[J]. Quality and Reliability Engineering International, 2010, 26 (3): 279- 289.
doi: 10.1002/qre.1056
17 LAUNGRUNGRONG B , BORROR C M , MONTGOMERY D C . EWMA control charts for multivariate Poisson-distributed data[J]. International Journal of Quality Engineering and Technology, 2011, 2 (3): 185.
doi: 10.1504/IJQET.2011.041227
18 STOUMBOS Z G , SULLIVAN J H . Robustness to non-normality of the multivariate EWMA control chart[J]. Journal of Quality Technology, 2002, 34 (3): 260- 276.
doi: 10.1080/00224065.2002.11980157
19 ZOU C L , TSUNG F . A multivariate sign EWMA control chart[J]. Technometrics, 2011, 53 (1): 84- 97.
doi: 10.1198/TECH.2010.09095
[1] CHEN Li, LIN Ling. Stock option pricing with time delay [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(4): 36-41.
[2] and PENG Shi-ge . Robust option pricing model and empirical performance [J]. J4, 2006, 41(2): 69-73 .
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] LUO Si-te, LU Li-qian, CUI Ruo-fei, ZHOU Wei-wei, LI Zeng-yong*. Monte-Carlo simulation of photons transmission at alcohol wavelength in  skin tissue and design of fiber optic probe[J]. J4, 2013, 48(1): 46 -50 .
[2] TIAN Xue-gang, WANG Shao-ying. Solutions to the operator equation AXB=C[J]. J4, 2010, 45(6): 74 -80 .
[3] HUO Yu-hong, JI Quan-bao. Synchronization analysis of oscillatory activities in a biological cell system[J]. J4, 2010, 45(6): 105 -110 .
[4] HE Hai-lun, CHEN Xiu-lan* . Circular dichroism detection of the effects of denaturants and buffers on the conformation of cold-adapted protease MCP-01 and  mesophilic protease BP01[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2013, 48(1): 23 -29 .
[5] SUN Xiao-ting1, JIN Lan2*. Application of DOSY in oligosaccharide mixture analysis[J]. J4, 2013, 48(1): 43 -45 .
[6] YANG Ying, JIANG Long*, SUO Xin-li. Choquet integral representation of premium functional and related properties on capacity space[J]. J4, 2013, 48(1): 78 -82 .
[7] Ming-Chit Liu. THE TWO GOLDBACH CONJECTURES[J]. J4, 2013, 48(2): 1 -14 .
[8] ZHAO Tong-xin1, LIU Lin-de1*, ZHANG Li1, PAN Cheng-chen2, JIA Xing-jun1. Pollinators and pollen polymorphism of  Wisteria sinensis (Sims) Sweet[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2014, 49(03): 1 -5 .
[9] WANG Kai-rong, GAO Pei-ting. Two mixed conjugate gradient methods based on DY[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2016, 51(6): 16 -23 .
[10] YANG Lun, XU Zheng-gang, WANG Hui*, CHEN Qi-mei, CHEN Wei, HU Yan-xia, SHI Yuan, ZHU Hong-lei, ZENG Yong-qing*. Silence of PID1 gene expression using RNA interference in C2C12 cell line[J]. J4, 2013, 48(1): 36 -42 .