From Exhaustive Vacation Queues to Preemptive Priority Queues with General Interarrival Times

Fiems, Dieter; Vuyst, Stijn De

doi:10.2478/amcs-2018-0053

Cited by 5 publications

(4 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this setting class, we can restrict our search for an optimal policy to the class of stationary policies (Fiems & De Vuyst, 2018). A stationary policy assigns actions based only on the current state of the system, regardless of the point in time at which the decision is being made.…”

Section: Model Formulationmentioning

confidence: 99%

simulation-based approach for minimizing waiting time in AIIMS, Delhi using Queuing model

Sharma

2022

ijhs

View full text Add to dashboard Cite

The government hospitals in India influenced by multiple factors causing longer waiting time of patients in comparison to private hospitals, which worsen the threat to healthcare facilities. The optimization of available resources considering the arrival rate of patients and the availability of facilities for the minimization of queuing is the utmost requirement. The current study has been carried out within the outpatient's department to minimize queue length of one of the largest and busiest hospital, AIIMS in Delhi, represent a struggling health care delivery system with high waiting times of patients. The primary queuing data was collected for total samples of 1200 patients during the four-week study period (1st July to 30th July 2020), (Monday-Friday) and working hours of general OPD (08:30 am to 01:00 pm). The detailed queuing secondary data was collected from AIIMS for three years (1st January 2015 to 31st July 2017). Data has been analyzed by queuing models, M/M/1: Poisson-exponential, single server model-infinite population and up to M/M/8: Poisson-exponential, multiple server model-infinite populations.

show abstract

Section: Model Formulationmentioning

confidence: 99%

simulation-based approach for minimizing waiting time in AIIMS, Delhi using Queuing model

Sharma

2022

ijhs

View full text Add to dashboard Cite

show abstract

“…These additional assumptions make research more complicated but let us successfully use introduced models in practice. Some aspects of customers' non-homogeneity have recently appeared in many works of researchers from different countries [4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Bulletin of the Polish Academy of Sciences: Technical Sciences

Ziółkowski,

Tikhonenko

2022

View full text Add to dashboard Cite

In the present paper, we analyze the model of a single-server queueing system with limited number of waiting positions, random volume customers and unlimited sectorized memory buffer. In such a system, the arriving customer is additionally characterized by a nonnegative random volume vector whose indications usually represent the portions of unchanged information of a different type that are located in sectors of unlimited memory space dedicated for them during customer presence in the system. When the server ends the service of a customer, information immediately leaves the buffer, releasing resources of the proper sectors. We assume that in the investigated model, the service time of a customer is dependent on his volume vector characteristics. For such defined model, we obtain a general formula for steady-state joint distribution function of the total volume vector in terms of Laplace-Stieltjes transforms. We also present practical results for some special cases of the model together with formulae for steady-state initial moments of the analyzed random vector, in cases where the memory buffer is composed of at most two sectors. Some numerical computations illustrating obtained theoretical results are attached as well.

show abstract

“…In this study, the preemptive repeat priority policy has been adopted for the prioritization of handoff calls over new calls. An overview of research works on the preemptive repeat PQM can be found in the articles (refer, [1,6,9,13], etc.). In these studies, challenges arising due to the consideration of the preemptive repeat policy have been emphasized.…”

Section: Introductionmentioning

confidence: 99%

Optimization of traffic control in MMAP[2]/PH[2]/S priority queueing model with PH retrial times and preemptive repeat policy

Raj,

Jain

2021

Preprint

View full text Add to dashboard Cite

The presented study elaborates a multi-server priority queueing model considering the preemptive repeat policy and phase-type distribution (PH) for retrial process. The incoming heterogeneous calls are categorized as handoff calls and new calls. The arrival and service processes of both types of calls follow marked Markoian arrival process (MMAP) and PH distribution with distinct parameters, respectively. An arriving new call will be blocked when all the channels are occupied, and consequently will join the orbit (virtual space) of infinite capacity to retry following PH distribution. When all the channels are occupied and a handoff call arrives at the system, out of the following two scenarios, one might take place. In the first scenario, if all the channels are occupied with handoff calls, the arriving handoff call will be lost from the system. While in the second one, if all the channels are occupied and at least one of them is serving a new call, the arriving handoff call will be provided service by using preemptive priority over that new call and the preempted new call will join the orbit. Behaviour of the proposed system is modelled by the level dependent quasi-birth-death (LDQBD) process.The expressions of various performance measures have been derived for the numerical illustration. An optimization problem for optimal channel allocation and traffic control has been formulated and dealt by employing appropriate heuristic approaches.

show abstract

From Exhaustive Vacation Queues to Preemptive Priority Queues with General Interarrival Times

Cited by 5 publications

References 49 publications

simulation-based approach for minimizing waiting time in AIIMS, Delhi using Queuing model

simulation-based approach for minimizing waiting time in AIIMS, Delhi using Queuing model

Bulletin of the Polish Academy of Sciences: Technical Sciences

Optimization of traffic control in MMAP[2]/PH[2]/S priority queueing model with PH retrial times and preemptive repeat policy

Contact Info

Product

Resources

About