The Discrete-Time Bulk-Service Geo/Geo/1

This paper deals with a discrete-time bulk-service Geo/Geo/1 queueing system with infinite buffer space and multiple working vacations. Considering an early arrival system, as soon as the server empties the system in a regular busy period, he leaves the system and takes a working vacation for a random duration at time n. The service times both in a working vacation and in a busy period and the vacation times are assumed to be geometrically distributed. By using embedded Markov chain approach and difference operator method, queue length of the whole system at random slots and the waiting time for an arriving customer are obtained. The queue length distributions of the outside observer’s observation epoch are investigated. Numerical experiment is performed to validate the analytical results

Optimization of renewal input (a, c, b) policy working vacation queue with change over time and bernoulli schedule vacation interruption

This paper presents a renewal input single working vacation queue with change over time and Bernoulli schedule vacation interruption under (a, c, b) policy. The service and vacation times are exponentially distributed. The server begins service if there are at least c units in the queue and the service takes place in batches with a minimum of size a and a maximum of size b (a ≤ c ≤ b). The change over period follows if there are (a − 1) customers at service completion instants. The steady state queue length distributions at arbitrary and pre-arrival epochs are obtained. An optimal cost policy is presented along with few numerical experiences. The genetic algorithm and quadratic fit search method are employed to search for optimal values of some important parameters of the system.Publisher's Versio

On transient queue-size distribution in the batch arrival system with the N-policy and setup times

In the paper the $M^{X}/G/1$ queueing system with the $N$-policy and setup times is considered. An explicit formula for the Laplace transform of the transient queue-size distribution is derived using the approach consisting of few steps. Firstly, a "special\u27\u27 modification of the original system is investigated and, using the formula of total probability, the analysis is reduced to the case of the corresponding system without limitation in the service. Next, a renewal process generated by successive busy cycles is used to obtain the general result. Sample numerical computations illustrating theoretical results are attached as well

On transient queue-size distribution in the batch arrival system with the N-policy and setup times

In the paper the $M^{X}/G/1$ queueing system with the $N$-policy and setup times is considered. An explicit formula for the Laplace transform of the transient queue-size distribution is derived using the approach consisting of few steps. Firstly, a "special\u27\u27 modification of the original system is investigated and, using the formula of total probability, the analysis is reduced to the case of the corresponding system without limitation in the service. Next, a renewal process generated by successive busy cycles is used to obtain the general result. Sample numerical computations illustrating theoretical results are attached as well

(R2053) Analysis of MAP/PH/1 Queueing Model Subject to Two-stage Vacation Policy with Imperfect Service, Setup Time, Breakdown, Delay Time, Phase Type Repair and Reneging Customer

In this paper, we study a continuous-time single server queueing system with an infinite system of capacity, a two-stage vacation policy with imperfect service, setup, breakdown, delay time, phase-type of repair and customer reneging. The Markovian Arrival Process is used for the arrival of a customer and the phase-type distribution is used when offering service. This encompasses the policy of two vacations: a single working vacation and multiple vacations. Using the Matrix-Analytic Method to approach the system generates an invariant probability vector for this model. Henceforth, the busy period, waiting time distribution and cost analysis are the additional findings. The indicators are secured as a result of this performance. The outcomes result of numerical order can be graphically interpreted in the form of 2D and 3D

Queueing models for appointment-driven systems.

Many service systems are appointment-driven. In such systems, customers make an appointment and join an external queue(also referred to as the “waiting list”). At the appointed date, the customer arrives at the service facility, joins an internal queue and receives service during a service session. After service, the customer leaves the system. Important measures of interest include the size of the waiting list, the waiting time at the service facility and server overtime. These performance measures may support strategic decisionmaking concerning server capacity (e.g. how often, when and for how long should a server be online). We develop an ew model to assess these performance measures. The model is a combination of a vacation queueing system and an appointment system.Queueing system; Appointment system; Vacation model; Overtime; Waiting list;