• 한국산업정보학회논문지
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• 제10권2호
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• pp.42-47
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• 2005

A single-server queueing model with the Batch Markovian Arrival Process and disaster ow correlated with the arrival process is analyzed. The numerically stable algorithm for calculating the steady state distribution of the system is presented.

• 한국산업정보학회논문지
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• 제12권4호
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• pp.107-118
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• 2007

A single-server queueing model with infinite buffer and batch arrival of customers is considered. In contrast to the standard batch arrival when a whole batch arrives into the system at one epoch, we assume that the customers of an accepted batch arrive one-by one in exponentially distributed times. Service time is exponentially distributed. Flow of batches is the stationary Poisson arrival process. Batch size distribution is geometric. The number of batches, which can be admitted into the system simultaneously, is subject of control. Analysis of the joint distribution of the number batches and customers in the system and sojourn time distribution is implemented by means of the matrix technique and method of catastrophes. Effect of control on the main performance measures of the system is demonstrated numerically.

• 대한산업공학회지
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• 제22권2호
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• pp.231-245
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• 1996

Semiconductor manufacturing line includes several batch processes which are to be controlled effectively to enhance the productivity of the line. The key problem in batch processes is a dynamic batch sizing problem which determines number of lots processed simultaneously in a single botch. The batch sizing problem in semiconductor manufacturing has to consider delay of lots, setup cost of the process, machine utilization and so on. However, an optimal solution cannot be attainable due to dynamic arrival pattern of lots, and difficulties in forecasting future arrival times of lots of the process. This paper proposes an efficient batch sizing heuristic, which considers delay cost, setup cost, and effect of the forecast errors in determining the botch size dynamically. Extensive numerical experiments through simulation are carried out to investigate the effectiveness of the proposed heuristic in four key performance criteria: average delay, variance of delay, overage lot size and total cost. The results show that the proposed heuristic works effectively and efficiently.

• 대한수학회논문집
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• 제32권2호
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• pp.425-433
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• 2017

This paper is concerned with the analysis of the busy period distribution in a batch arrival $M^X/G/1$ retrial queue. The expression for the Laplace-Stieltjes transform of the length of the busy period is well known, but from this expression we cannot compute the moments of the length of the busy period by direct differentiation. This paper provides a direct method of calculation for the first and second moments of the length of the busy period.

• 대한산업공학회지
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• 제28권1호
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• pp.36-43
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• 2002

We analyze bulk service $M/G^{b}/1$ queues using the arrival time approach of Chae et al. (2001). As a result, the decomposition property of the M/G/1 queue with generalized vacations is extended to the $M/G^{b}/1$ queue in which the batch size is exactly a constant b. We also demonstrate that the arrival time approach is useful for relating the time-average queue length PGF to that of the departure time, both for the $M/G^{b}/1$queue in which the batch size is as big as possible but up to the maximum of constant b. The case that the batch size is a random variable is also briefly mentioned.

• 한국통신학회논문지
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• 제25권9A호
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• pp.1377-1386
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• 2000

As all delays resulting from the signaling network directly affect the response time of network management activity, all control informations have to be transported most efficiently. It is very important to know the performance of the signaling system not only because of smooth network operation but also because of efficient engineering of signaling networks. In this paper, we analyzed mean queueing delay of signaling link for ISUP signaling messages in common channel signaling system by using M[X]/G/1 and M[X]/D/1 batch arrival queueing system. This is because we modeled arrival process of the signaling messages as batch arrival process considering that many kinds of signaling messages are generated at short intervals when a call requests a connection. Analysis was carried out considering different call processing scenario based on ITU-T specification. We also described the numerical results from the different types of queueing models.

• Management Science and Financial Engineering
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• 제12권2호
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• pp.1-18
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• 2006

We consider an $M^x/G/1$ queueing system with Bernoulli vacation schedule under multiple vacation policy. where after each vacation completion or service completion the server takes sequence of vacations until a batch of new customer arrive. This generalizes both $M^x/G/1$ queueing system with multiple vacation as well as M/G/1 Bernoulli vacation model. We carryout an extensive analysis for the queue size distributions at various epochs. Further attempts have been made to unify the results of related batch arrival vacation models.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1993년도 춘계공동학술대회 발표논문 및 초록집; 계명대학교, 대구; 30 Apr.-1 May 1993
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• pp.58-58
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• 1993

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.271-275
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• 2005

Queueing models are good models for fragments of communication systems and networks, so their investigation is interesting for theory and applications. Theses queues may play an important role for the validation of different decomposition algorithms designed for investigating more general queueing networks. So, in this paper we illustrate that the batch size distribution affects the loss probability, which is the main performance measure of a finite buffer queues.

• 한국산업정보학회논문지
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• 제11권1호
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• pp.1-6
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• 2006

Queueing models are good models for fragments of communication systems and networks, so their investigation is interesting for theory and applications. Theses queues may play an important role for the validation of different decomposition algorithms designed for investigating more general queueing networks. So, in this paper we illustrate that the batch size distribution affects the loss probability, which is the main performance measure of a finite buffer queues.