On a retrial queue with negative customers, passive breakdown, and delayed repairs

IF 0.7 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL Probability in the Engineering and Informational Sciences Pub Date : 2023-10-20 DOI:10.1017/s0269964823000219
Yunna Han, Ruiling Tian, Xinyu Wu, Liuqing He
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Abstract

Abstract This paper studies an M/M/1 retrial queue with negative customers, passive breakdown, and delayed repairs. Assume that the breakdown behavior of the server during idle periods is different from that during busy periods. Passive breakdowns may occur when the server is idle, due to the lack of monitoring of the server during idle periods. When the passive breakdown occurs, the server does not get repaired immediately and enters a delayed repair phase. Negative customers arrive during the busy period, which will cause the server to break down and remove the serving customers. Under steady-state conditions, we obtain explicit expressions of the probability generating functions for the steady-state distribution, together with some important performance measures for the system. In addition, we present some numerical examples to illustrate the effects of some system parameters on important performance measures and the cost function. Finally, based on the reward-cost structure, we discuss Nash equilibrium and socially optimal strategy and numerically analyze the influence of system parameters on optimal strategies and optimal social benefits.
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在有负面客户、被动故障和延迟维修的重审队列上
摘要研究了一类具有负顾客、被动故障和延迟维修的M/M/1重审队列。假设服务器在空闲期间的故障行为与繁忙期间的故障行为不同。当服务器处于空闲状态时,由于在空闲期间缺乏对服务器的监控,可能会发生被动故障。当被动故障发生时,服务器不会立即得到修复,而是进入延迟修复阶段。负面客户在繁忙期间到来,这会导致服务器崩溃,并移除正在服务的客户。在稳态条件下,我们得到了稳态分布的概率生成函数的显式表达式,以及系统的一些重要性能指标。此外,我们还给出了一些数值例子来说明一些系统参数对重要性能指标和成本函数的影响。最后,基于回报-成本结构,讨论了纳什均衡和社会最优策略,并数值分析了系统参数对最优策略和最优社会效益的影响。
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来源期刊
CiteScore
2.20
自引率
18.20%
发文量
45
审稿时长
>12 weeks
期刊介绍: The primary focus of the journal is on stochastic modelling in the physical and engineering sciences, with particular emphasis on queueing theory, reliability theory, inventory theory, simulation, mathematical finance and probabilistic networks and graphs. Papers on analytic properties and related disciplines are also considered, as well as more general papers on applied and computational probability, if appropriate. Readers include academics working in statistics, operations research, computer science, engineering, management science and physical sciences as well as industrial practitioners engaged in telecommunications, computer science, financial engineering, operations research and management science.
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