• Journal of the Korean Statistical Society
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• v.21 no.1
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• pp.47-58
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• 1992

The autocorrelation function structures of bilinear time series model BL(p, q, r, s), $r \geq s$ are obtained and shown to be analogous to those of ARMA(p, l), l=max(q, s). Simulation studies are performed to investigate the adequacy of Akaike information criteria for identification between ARMA(p, l) and BL(p, q, r, s) models and for determination of orders of BL(p, q, r, s) models. It is suggested that the model of having minimum Akaike information criteria is selected for a suitable model.

• Journal of the Korean Operations Research and Management Science Society
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• v.11 no.1
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• pp.44-50
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• 1986

In this paper, we find optimal policy for the (Q, r) inventory model under the lead time uncertainty. The (Q, r) inventory model is such that the fixed order quantity Q is placed whenever the level of on hand stock reaches the reorder point r. We first develop the single level inventory model as the basis for the analysis multi-level distribution systems. The functional problem is to determine when and how much to order in order to minimize the expected total cost per unit time, which includes the set up, inventory holding and inventory shortage cost. The model, then, is extended to the multi-level distribution system consisting of the factory, warehouses and retailers. In this case, we also find an optimal policy which minimizes the total cost of the contralized multi-level distribution system.

• Journal of the Korean Statistical Society
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• v.8 no.2
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• pp.107-109
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• 1979

Consider a linear model with n observations and k explanatory variables: (1)b $y=X\beta+u, u\simN(0,\sigma^2I_n)$. We assume that the model satisfies the ideal conditions. Consider the general linear constraints on regression coefficient vector: (2) $R\beta=r$, where R and r are known matrices of orders $q\timesk$ and q\times1$ respectively, and the rank of R is $qk+q$.

• Geomechanics and Engineering
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• v.29 no.5
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• pp.487-496
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• 2022

Most of the pile's vertical static load tests in construction sites are the proof load tests, which is difficult to accurately estimate the ultimate bearing capacity and analyze the reliability of piles. Therefore, a reliability analysis method based on the proof load-settlement (Q-s) data is proposed in this study. In this proposed method, a simple ultimate limit state function based on the hyperbolic model is established, where the random variables of reliability analysis include the model factor of the ultimate bearing capacity and the fitting parameters of the hyperbolic model. The model factor M = R_uR / R_uP is calculated based on the available destructive Q-s data, where the real value of the ultimate bearing capacity (R_uR) is obtained by the complete destructive Q-s data; the predicted value of the ultimate bearing capacity (R_uP) is obtained by the proof Q-s data, a part of the available destructive Q-s data, that before the predetermined load determined by the pile test report. The results demonstrate that the proposed method can easy and effectively perform the reliability analysis based on the proof Q-s data.

• Management Science and Financial Engineering
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• v.15 no.1
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• pp.33-49
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• 2009

We examine the effectiveness of the conventional (Q, r) model in managing production-inventory systems with finite capacity, stochastic demand, and stochastic order processing times. We show that, for systems with finite production capacity, order replenishment lead times are highly sensitive to loading and order quantity. Consequently, the choice of optimal order quantity and optimal reorder point can vary significantly from those obtained under the usual assumption of a load-independent lead time. More importantly, we show that for a given (Q, r) policy the conventional model can grossly under or over-estimate the actual cost of the policy. In cases where a setup time is associated with placing a production order, we show that the optimal (Q, r) policy derived from the conventional model can, in fact, be infeasible.

• Electronics and Telecommunications Trends
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• v.30 no.1
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• pp.154-161
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• 2015

본고에서는 Q-mark 모델의 R&D(Research & Development) 품질 영향 분석을 기술한다. 이를 위해 Q-mark 모델 특징과 종류 그리고 절차를 간략히 기술하고, R&D 품질에 대한 Q-mark 인증 모델 영향에 대해 연구현장 설문조사 내용을 바탕으로 연구결과 완성도 측면, 대외 신뢰도 개선을 통한 과제 수주 측면, 기술 이전과 사업화 측면, 그리고 과제관리 효율화 측면 등에서 분석하여 제시한다. 또 앞으로 Q-mark 모델이 보다 객관적이고 효과적인 R&D 품질관리를 위한 인증 모델로 개선되고 지속적으로 운영되기 위해 보완되어야 할 사항에 대해 설문조사 결과를 바탕으로 인증 측면, 프로세스 범주 측면, 제공 템플릿 측면, 그리고 품질 지원 서비스 및 전문성 측면에서 기술한다.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.43-65
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• 1998

This paper develops a two-echelon inventory model with time-weighted partial backorders. The presented model assumed to follow continuous review (Q. r) policy for both the retailers and the central warehouse under stochastic demand. A heuristic method to find an optimum-tending solution for total variable system cost per year incurred at the central warehouse and retailers in a system is suggested. To show the usefulness of the above model, numericla examples are illustrated for verification and validation purpose.

• Journal of Korean Society for Quality Management
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• v.24 no.1
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• pp.44-49
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• 1996

This paper deals with a (Q, r) spare-part inventory model with gamma leadtime. In the model, if the inventory level falls to a reorder point r, a replenishment order quantity Q is ordered. Assumming that the number of operating units is one and the lifetime of a unit follows an exponential distribution, we derive the expected cost rate and suggest a procedure to obtain the optimal pair of (Q, r) minimizing the cost rate. A numerical example is presented to explain the model.

• Journal of Ginseng Research
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• v.33 no.3
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• pp.240-243
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• 2009

To better understand how to increase a ginseng grower's revenue, a 4-factor revenue determination model (RDM) of raw ginseng production (R=A Y Q P) was proposed. The total revenue (R) is a multiplicative function of four factors: cultivation area(A), unit yield (Y), quality grade (Q) and unit price (P). The A appears to be a pure capital factor. Y and Q are technological factors and P is social and market factor. When P is constant, the technological term (YQ) is the revenue per unit area (R/A) production efficiency per capital. The RDM appears to be a linear model between R and A with the slope [YQ]. RDM was applied to three farmers' raw ginseng production for assessment of its dependency on capital and technological factors.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.27-46
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• 1992

This paper considers an (r, Q) policy for operation of a multipurpose facility. It is assumed that whenever the inventory level falls below r, the model starts to produce the fixed amount of Q. The facility can be utilized for extra production during idle periods, that is, when the inventory level is still greater than r right after a main production operation is terminated or an extra production operation is finished. But, whenever the facility is in operation for an extra production, the operation can not be terminated for the main production even though the inventory level falls below r. In the model, the demand for the product is assumed to arrive according to a compound Poisson process and the processing time required to produce a product is assumed to follow an arbitary distribution. Similarly, the orders for the extra production is assumed to accur in a Poisson process are the extra production processing time is assumed to follow an arbitrary distribution. It is further assumed that unsatisfied demands are backordered and the expected comulative amount of demands is less than that of production during each production period. Under a cost structure which includes a setup/ production cost, a linear holding cost, a linear backorder cost, a linear extra production lost sale cost, and a linear extra production profit, an expression for the expected cost per unit time for a given (r, Q) policy is obtained, and using a convex property of the cost function, a procedure to find the optimal (r, Q) policy is presented.