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IJSOM 2014, 1(1): 1-19 Back to browse issues page
Analysis of an M/G/1 Queue with Multiple Vacations, N-policy, Unreliable Service Station and Repair Facility Failures
Wenqing Wu *1, Yinghui Tang 2, Miaomiao Yu 3
1- School of Mathematics & Software Science, Sichuan Normal University, Chengdu, Sichuan, 610068, China , wwqing0704@swust.edu.cn
2- School of Mathematics & Software Science, Sichuan Normal University, Chengdu, Sichuan, 610068, China
3- School of Science, Sichuan University of Science and Engineering, Zigong, Sichuan, 643000, China
Abstract:   (3276 Views)
This paper studies an M/G/1 repairable queueing system with multiple vacations and N-policy, in which the service station is subject to occasional random breakdowns. When the service station breaks down, it is repaired by a repair facility. Moreover, the repair facility may fail during the repair period of the service station. The failed repair facility resumes repair after completion of its replacement. Under these assumptions, applying a simple method, the probability that the service station is broken, the rate of occurrence of breakdowns of the service station, the probability that the repair facility is being replaced and the rate of occurrence of failures of the repair facility along with other performance measures are obtained. Following the construction of the long-run expected cost function per unit time, the direct search method is implemented for determining the optimum threshold N* that minimises the cost function.
Keywords: M G 1 repairable queue, Multiple vacations, Min (N, V)-policy, Reliability measure, Cost function
     
Type of Study: مقاله پژوهشی |
ePublished: 2017/09/28
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Wu W, Tang Y, Yu M. Analysis of an M/G/1 Queue with Multiple Vacations, N-policy, Unreliable Service Station and Repair Facility Failures. IJSOM. 2014; 1 (1) :1-19
URL: http://system.khu.ac.ir/ijsom/article-1-1900-en.html
issue 1, Issue 1 (5-2014) Back to browse issues page
International Journal of Supply and Operations Management International Journal of Supply and Operations Management
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