• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.81-90
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• 2016

Different from general operating policies to be applied for controllable queueing models, two of three well-known simple N, T and D operating policies are applied alternatingly to the single server controllable queueing models, so called alternating (NT), (ND) and (TD) policies. For example, the alternating (ND) operating policy is defined as the busy period is initiated by the simple N operating policy first, then the next busy period is initiated by the simple D operating policy and repeats the same sequence after that continuously. Because of newly designed operating policies, important system characteristic such as the expected busy and idle periods, the expected busy cycle, the expected number of customers in the system and so on should be redefined. That is, the expected busy and idle periods are redefined as the sum of the corresponding expected busy periods and idle periods initiated by both one of the two simple operating policies and the remaining simple operating policy, respectively. The expected number of customers in the system is represented by the weighted or pooled average of both expected number of customers in the system when the predetermined two simple operating policies are applied in sequence repeatedly. In particular, the expected number of customers in the system could be used to derive the expected waiting time in the queue or system by applying the famous Little's formulas. Most of such system characteristics derived would play important roles to construct the total cost functions per unit time for determination of the optimal operating policies by defining appropriate cost elements to operate the desired queueing systems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.1
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• pp.96-103
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• 2014

A steady-state controllable M/G/1 queueing model operating under the (TN) policy is considered where the (TN) policy is defined as the next busy period will be initiated either after T time units elapsed from the end of the previous busy period if at least one customer arrives at the system during that time period, or the time instant when Nth customer arrives at the system after T time units elapsed without customers' arrivals during that time period. After deriving the necessary system characteristics such as the expected number of customers in the system, the expected length of busy period and so on, the total expected cost function per unit time in the system operation is constructed to determine the optimal operating policy. To do so, the cost elements associated with such system characteristics including the customers' waiting cost in the system and the server's removal and activating cost are defined. Then, the optimal values of the decision variables included in the operating policies are determined by minimizing the total expected cost function per unit time to operate the system under consideration.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.71-77
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• 2009

Using the results of the expected busy periods for the dyadic Min(N, D) and Max(N, D) operating policies in a controllable M/G/1 queueing model, an important relation between them is derived. The derived relation represents the complementary property between two operating policies. This implies that it could be possible to obtained desired system characteristics for one of the two operating policies from the corresponding known system characteristics for the other policy. Then, upper and lower bounds of expected busy periods for both dyadic operating policies are also derived.

• Journal of applied mathematics & informatics
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• v.5 no.1
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• pp.1-12
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• 1998

We consider G/M/1 queues with multiple vacation disci-pline where at the end of every busy period the server stays idle in the system for a period of time called changeover time and then follows a vacation if there is no arrival during the changeover time. The vaca-tion time has a hyperexponential distribution. By using the methods of the shift operator and supplementary variable we explicitly obtain the queue length probabilities at arrival time points and arbitrary time points simultaneously.

• Communications of the Korean Mathematical Society
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• v.13 no.2
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• pp.393-403
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• 1998

We consider $M_1,M_2/M/1$ retrial queues with two classes of customers in which the service rates depend on the total number or the customers served since the beginning of the current busy period. In the case that arriving customers are bloced due to the channel being busy, the class 1 customers are queued in the priority group and are served as soon as the channel is free, whereas the class 2 customers enter the retrical group in order to try service again after a random amount of time. For the first $N(N \geq 1)$ exceptional services model which is a special case of our model, we derive the joint generating function of the numbers of customers in the two groups. When N = 1 i.e., the first exceptional service model, we obtain the joint generating function explicitly and if the arrival rate of class 2 customers is 0, we show that the results for our model coincide with known results for the M/M/1 queues with smart machine.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.2
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• pp.187-192
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• 2002

In this paper we consider an M/G/1 queueing system with vacation. The length of vacation period may be controlled by the waiting time of the first customer. The server goes on vacation as soon as the system is empty, and resumes service either when the waiting time of the leading customer reaches a predetermined value, or when the vacation period is expired, whichever comes first. We consider two types of vacation, say, multiple vacation type and N-policy type. We derive the steady-state distributions of the number of customers at arbitrary time and arbitrary customer's waiting time by means of decomposition property. Also, the mean lengths of busy period, idle period and a cycle time are given.

• Journal of the Korean Mathematical Society
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• v.35 no.3
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• pp.503-525
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• 1998

In the theory of retrial queues it is usually assumed that the flow of primary customers is Poisson. This means that the number of independent sources, or potential customers, is infinite and each of them generates primary arrivals very seldom. We consider now retrial queueing systems with a homogeneous population, that is, we assume that a finite number K of identical sources generates the so called quasi-random input. We present a survey of the main results and mathematical tools for finite source retrial queues, concentrating on M/G/1//K and M/M/c//K systems with repeated attempts.

• Journal of the Korean Statistical Society
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• v.28 no.4
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• pp.523-533
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• 1999

We consider the M/G/1 queueing model with D-policy. The server is turned off at the end of each busy period and is activated again only when the sum of the service times of all waiting customers exceeds a fixed value D. We obtain the distribution of unfinished work and show that the unfinished work decomposes into two random variables, one of which is the unfinished work of ordinary M/G/1 queue. We also derive the distribution of queue waiting time.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.289-294
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• 2004

We consider M/G/1 queue in which the customers are classified into n+1 classes by their impatience time. First, we analyze the model of two types of customers; one is the customer with constant impatience duration k and the other is patient customer. The expected busy period of the server and the limiting distribution of the virtual waiting time process are obtained. Then, the model is generalized to the one in which there are classes of customers according to their impatience duration.

• Journal of the Korean Statistical Society
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• v.33 no.2
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• pp.159-167
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• 2004

We present a simple approach to finding the stationary workload of M/G/1 queues having generalized vacations and exhaustive service discipline. The approach is based on the level crossing technique. According to the approach, all that we need is the workload at the beginning of a busy period. An example system to which we apply the approach is the M/G/1 queue with both multiple vacations and D-policy.