• 한국경영과학회지
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• 제37권2호
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• pp.31-43
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• 2012

Delivery of a good quality of service in an efficient manner requires matching the supply of capacity with customer demand. Much research has employed queueing models that analyzed the service system on the basis of independent and stationary customer arrivals. However, the appointment system, which is widely used to facilitate customer access to service in many industries including healthcare, has significant influence on the customer arrival process so that the independent and stationary assumption does not hold in an appointment-based service system. In this regard, this paper aims to propose a model for accurate illustration of the appointment-based customer arrival process. The use of the proposed model allows us to evaluate the overall system performance such as mean waiting time and service level under various appointment policies instead of conducting simulation studies.

• 경영과학
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• 제32권2호
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• pp.69-78
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• 2015

This paper considers a Bayesian Poisson model for multivariate count data using multiplicative rates. More specifically we compose the parameter for overall arrival rates by the product of two parameters, a common effect and an individual effect. The common effect is composed of autoregressive evolution of the parameter, which allows for analysis on seasonal effects on all multivariate time series. In addition, analysis on individual effects allows the researcher to differentiate the time series by whatevercharacterization of their choice. This type of model allows the researcher to specifically analyze two different forms of effects separately and produce a more robust result. We illustrate a simple MCMC generation combined with a Gibbs sampler step in estimating the posterior joint distribution of all parameters in the model. On the whole, the model presented in this study is an intuitive model which may handle complicated problems, and we highlight the properties and possible applications of the model with an example, analyzing real time series data involving customer arrivals to a large retail store.

• 산업공학
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• 제14권4호
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• pp.365-373
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• 2001

It is discussed how to determine time windows for pickups and deliveries, which have been assumed to be given in all most of previous studies on traveling salesman problems with time window, vehicle routing problems with time window, vehicle scheduling and dispatching problems, and so on. First, time windows are classified into four models (DR, DA, AR, and AA) by customers‘ polices. For each model, it is shown how a time window is related to various cost terms of suppliers and customers. Under the assumption of collaborative supplier-customer relationship, an integrated cost model for both supplier and customer is constructed for determining boundaries of time windows. The cost models in this paper consists of cost terms that depend on waiting time, early arrival time, late arrival time, and rejection of receipt. A numerical example is provided and results of the sensitivity analysis for some parameters are also provided to help intuitive understanding about the characteristics of the suggested models.

• 한국경영과학회지
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• 제37권4호
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• pp.73-93
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• 2012

In recent years, service delivery systems employing a self-service approach have been rapidly spreading. Since a self-service system provides a lower product price, it attracts more customers. However, some system managers are still hesitant to accept a self-service system, because there is no systematic model to predict its performance. Therefore, this research attempts to provide a systematic and quantitative model to predict the performance of a self-service system, focused specifically on a self-service gas station. Under this model, the traditional queuing theory was adopted to describe the general self-service process, but it is also assumed that some changes occur in both the customer arrival rate and the service performance rate. In particular, the price elasticity was introduced to capture the change in the customer arrival rate, and the existence of learning effect and helpers were assumed to design the changed service performance rate. Under these assumptions, a simulation model for a self-service gas station is established, and three performance measurements, such as average number of customers, average waiting time, and Utilization are observed, depending on the changes in price difference and helper-operating time. In this research, the optimal operation strategy for price differentiation and helper-operating time is proposed in accordance with the level of the customer learning rate. Although this research confines the scope of the study to the self-service gas station model, the results of this research can be applied to any type of self-service system.

• Journal of the Korean Statistical Society
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• 제28권1호
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• pp.125-133
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• 1999

We consider a FIFO single-server queueing model in which both the arrival and service processes are modulated by the amount of work in the system. The arrival process is a non-homogeneous Poisson process(NHPP) modulated by work, that is, with an intensity that depends on the work in the system. Each customer brings a job consisting of an exponentially distributed amount of work to be processed. The server processes the work at various service rates which also depend on the work in the system. Under the stability conditions obtained by Browne and Sigman(1992) we derive the exact stationary distribution of the work W(t) and the first exit probability that the work level b is exceeded before the work level a is reached, starting from x$\in$[a, b].

• 산업경영시스템학회지
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• 제38권1호
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• pp.21-29
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• 2015

A steady-state controllable M/G/1 queueing model operating under the {T:Min(T,N)} policy is considered where the {T:Min(T,N)} 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 after T time units elapsed without a customer' arrival, the time instant when Nth customer arrives at the system or T time units elapsed with at least one customer arrives at the system whichever comes first. After deriving the necessary system characteristics including 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 for 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, procedures to determine the optimal values of the decision variables included in the operating policy are provided based on minimizing the total expected cost function per unit time to operate the queueing system under considerations.

• Industrial Engineering and Management Systems
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• 제15권2호
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• pp.131-142
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• 2016

We consider a multi-server queueing system without buffer and with two types of customers as a model of operation of a mobile network cell. Customers arrive at the system in the marked Markovian arrival flow. The service times of customers are exponentially distributed with parameters depending on the type of customer. A part of the available servers is reserved exclusively for service of first type customers. Customers who do not receive service upon arrival, can make repeated attempts. The system operation is influenced by random factors, leading to a change of the system parameters, including the total number of servers and the number of reserved servers. The behavior of the system is described by the multi-dimensional Markov chain. The generator of this Markov chain is constructed and the ergodicity condition is derived. Formulas for computation of the main performance measures of the system based on the stationary distribution of the Markov chain are derived. Numerical examples are presented.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 추계학술대회 논문집
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• pp.1881-1888
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• 2008

As the ticket issuing methods have been diversified for the convenience of the passengers such as ticketless service(SMS ticket, e-ticket, home ticket), automatic ticket issuing machine and consignment ticket sale, maintaining the current number of ticket booth has been becoming a issue. Too many booth can cause the inefficiency of the cost of labor. According to the Charter of Customer Service of Korail, on the other hand, 95% of passengers have to purchase a train ticket within 5 minutes. This study was designed to present a decision making model for the optimum number of ticket booth which can affect an efficient operation of train station and improvement of customer convenience. And, this paper shows the proper manpower of ticket booth and the change of customer waiting time by analyzing the arrival and ticket issuing time of passengers based on 'Queueing Theory'. However, it is insufficient to be generalized due to some limitations of analysis. This study will contribute to improve customer satisfaction by reducing the waiting time at the ticket booth. In addition, presenting the optimum number of booth is expected to have an effect on the increase of productivity and cost savings.

• 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.

• Industrial Engineering and Management Systems
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• 제12권3호
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• pp.207-223
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• 2013

Revenue management (RM) has been widely used to model products characterized as perishable. Classical RM model assumed that price is the sole factor in the model. Thus price adjustment becomes a crucial and costly factor in business. In this paper, an optimal pricing model is developed based on minimization of soft customer cost, one kind of price adjustment cost and is solved by Lagrange multiplier method. It is formed by expected discounted revenue/bid price integrating quantity-based RM and pricing-based RM. Quantity-based RM consists of two capacity models, namely, booking limit and overbooking. Booking limit, built by assuming uncertain customer arrival, decides the optimal capacity allocation for two market segments. Overbooking determines the level of accepted order exceeding capacity to anticipate probability of cancellation. Furthermore, pricing-based RM models occupancy/demand rate influenced by internal and competitor price changes. In this paper, a mathematical model based on game theoretic approach is developed for two conditions of deterministic and stochastic demand. Based on the equilibrium point, the best strategy for both hotels can be determined.