Interrelationship between controlling arrival and service in queueing systems

Gupta, Surendra M.

doi:10.1016/0305-0548(94)00088-p

Cited by 72 publications

(20 citation statements)

References 9 publications

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“…The developments and applications on service control of queueing systems are rich and varied (see Tadj and Choudhury [9]). In the other hand, F-policy, the pioneering work in the issue of controlling the arrivals, was first investigated by Gupta [10]. The intention of the F-policy is to control the arrival process when service control is not possible through N-policy.…”

Section: Introductionmentioning

confidence: 98%

Randomized controlling arrival for a queueing system with subject to server breakdowns

Chang

2013

Optimization

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This paper considers the optimal management problem of a finite-capacity M/M/1/K queueing system with h p; Fi-policy in which the server may break down while working. When the number of customers reaches its capacity K, no further arriving customers are allowed to enter the system. Customers are allowed to system with probability p or the customers are still unable to enter the system with probability 1 À p as the queue length decreases to a certain threshold value F. By applying the birth-and-death process, some important performance measures are derived. A cost model, developed to determine the optimal continuous and discrete control parameters for the h p; Fi-policy at a minimum cost, and sensitivity analysis are also studied.

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Section: Introductionmentioning

confidence: 98%

Randomized controlling arrival for a queueing system with subject to server breakdowns

Chang

2013

Optimization

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“…The developments and applications on service control of queueing systems are rich and varied [15]. On the other hand, F-policy, the pioneering work in the issue of controlling the arrivals, was first investigated by Gupta [5]. Later, the F-policy M/M/1 queueing system with second optional services was investigated by Ke et al [8].…”

Section: Introductionmentioning

confidence: 99%

The optimal management of a queueing system with controlling arrivals

Chang

Huang

2011

Journal of the Chinese Institute of Industrial Engineers

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This article considers the optimal management problem of a finite capacity M/H 2 /1 queueing system, in which the unreliable server operates the F-policy. When the number of customers in the system reaches its capacity K (K 5 1), no further arriving customers are allowed to enter the system until a certain number of customers who are already in the system have been served so that the number of customers in the system decreases to a predetermined threshold F (0 F K À 1). At that time, the server needs to take an exponential startup time and allow customers to enter the system. The F-policy investigates the most common issue of controlling arrival to a queueing system and a startup time is required before allowing customers to enter the system. This system is useful in many potential applications for wireless communication networks, transportation service systems, and production systems. Some important performance measures are derived. A cost model, developed to determine the optimal capacity K, the optimal threshold F, the optimal setup rate, and the optimal repair rate at a minimum cost, is also studied.

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“…The other day-to-day realistic applications of F-policy for the machining system can be found in many machine repair shops namely automobile repair shop. Gupta [10] introduced the concept of F-policy to study Markovian single server model. According to F-policy, as the system reaches to its full capacity, no further units are permitted to enter in the system until the number of units again drops to a prefixed threshold value 'F'.…”

Section: Introductionmentioning

confidence: 99%

Performance Modeling and ANFIS Computing for Finite Buffer Retrial Queue Under F-Policy

Jain

Sanga

2017

Advances in Intelligent Systems and Computing

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Abstract. This investigation is concerned with the performance prediction and admission control F-policy for the machine repair problem with retrial. To develop a Markov model, the steady state Chapman-Kolmogorov equations are constructed. The system state probabilities are obtained by using recursive method. Various performance measures are established explicitly in terms of steady state probabilities. To examine the effects of system parameters, the numerical simulation is performed by choosing a suitable illustration. The cost function is also framed to evaluate the optimal service rate and corresponding optimal cost. ANFIS soft computing technique is used to compare the numerical results obtained analytically and also by implementing ANFIS.

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Interrelationship between controlling arrival and service in queueing systems

Cited by 72 publications

References 9 publications

Randomized controlling arrival for a queueing system with subject to server breakdowns

Randomized controlling arrival for a queueing system with subject to server breakdowns

The optimal management of a queueing system with controlling arrivals

Performance Modeling and ANFIS Computing for Finite Buffer Retrial Queue Under F-Policy

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