• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2840-2853
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• 2015

A major challenge in network service providers is to provide adequate resources in service level agreements based on forecasts of future demands. In this paper, we address the problem of capacity provisioning in a network subject to demand uncertainty such that a network coded multicast is applied as the data delivery mechanism with limited budget to purchase extra capacity. We address some particular type of uncertainty sets that obtain a tractable constrained capacity provisioning problem. For this reason, we first formulate a mathematical model for the problem under uncertain demand. Then, a robust optimization model is proposed for the problem to optimize the worst-case system performance. The robustness and effectiveness of the developed model are demonstrated by numerical results. The robust solution achieves more than 10% reduction and is better than the deterministic solution in the worst case.

• 대한안전경영과학회지
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• 제8권5호
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• pp.139-150
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• 2006

The aim of this study is to establish an efficient distribution planning for a capacitated multi-stage supply chain. We assume that the demand information during planning horizon is given a deterministic form using a certain forecasting method. Under such a condition, we present a cost effective heuristic method for minimizing chain-wide supply chain inventory cost that is the sum of holding and backorder costs by using look-ahead technique. We cope with the capacity restriction constraints through look-ahead technique that considers not only the current demand information but also future demand information. To evaluate performance of the proposed heuristic method, we compared it with the extant research that utilizes echelon stock concept, under various supply chain settings.

• 대한교통학회:학술대회논문집
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• 대한교통학회 2000년도 제37회 학술발표회논문집
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• pp.89-115
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• 2000

Traffic signal setting policies and traffic assignment procedures are mutually dependent. The combined signal control and traffic assignment problem deals with this interaction. With the total travel time minimization objective, gradient based local search methods are implemented. Deterministic user equilibrium is the selected user route choice rule, Webster's delay curve is the link performance function, and green time per cycle ratios are decision variables. Three implemented solution codes resulting in six variations include intersections operating under multiphase operation with overlapping traffic movements. For reference, the iterative approach is also coded and all codes are tested in four example networks at five demand levels. The results show the numerical gradient estimation procedure performs best although the simplified local searches show reducing the large network computational burden. Demand level as well as network size affects the relative performance of the local and iterative approaches. As demand level becomes higher, (1) in the small network, the local search tends to outperform the iterative search and (2) in the large network, vice versa.

• 한국산업정보학회논문지
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• 제4권4호
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• pp.32-39
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• 1999

주문형 비디오 시스템에서 가변 비트율로 압축된 데이타들은 압축 대상이 되는 데이타의 내용 변화와 압축 기법의 특성으로 인해 단위 시간 당 처리해야 할 데이타 크기가 일정하지 않다. 그러나, 대부분의 주문형 비디오 서버들은 가변 비트율로 압축된 데이타를 실시간에 처리하기 위해 가변 데이타 크기의 최대값으로 시스템 자원을 예약하기 때문에 자원의 활용률이 떨어진다. 본 논문에서는 주문형 비디오 서버에서 시스템 자원의 활용률을 향상시켜 더 많은 사용자를 수용할 수 있는 버퍼 관리 기법을 제안한다. 제안된 버퍼 관리 기법은 데이타에 대한 캐슁 기법과 함께 가변 비트율로 압축된 데이타를 예약할 때 선반입 기법을 적용함으로써 비디오 데이타의 가변성을 줄이고 디스크 대역폭과 서버 버퍼에 대한 활용률을 극대화하였다. 본 논문에서 제안한 버퍼 관리 기법의 효율성은 모의 실험을 통해 확인하였다.

• 한국시뮬레이션학회논문지
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• 제15권3호
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• pp.39-47
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• 2006

대부분의 공급망 계획에서 사용되는 각 계획 기간 내의 예측수요는 확정적인 것으로 간주한다. 그러나 현실에서 주어진 계획 기간 내의 수요 예측값은 확률적으로 분포를 따르는 것이 일반적이다. 본 연구는 기존의 안전재고를 통한 서비스 수준을 관리하는 방법을 대신하여 고객 수요의 분포내의 특정한 값을 수요 예측값으로 사용하는 수요선택 방법에 대해 다룬다. 수요 분위수와 계층 재고의 개념을 활용하여 서비스 수준 제약이 존재하는 시리얼 재고시스템을 대상으로 비교적 간단하지만 효과적인 수요선택을 위한 휴리스틱 알고리듬을 제안한다. 시뮬레이션을 활용한 비교 실험을 통해 제안된 알고리듬이 최적해와 유사한 매우 정확한 결과를 보임을 입증하였다.

• 경영과학
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• 제29권3호
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• pp.121-134
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• 2012

In this study, we consider a component procurement planning problem where the procurement amounts of components are determined under assemble-to-order systems with demand uncertainty. In the problem, procurement amount of each component is decided before the demands of finished products are known and after the demands are identified the assembly amounts of the finished products are decided. In this study, the objective function of the problem is minimizing the total costs which are composed of purchase and inventory costs of the components and the backorder costs of the finished products. We assume that the uncertain demand information is given as multiple scenarios of the demands, and we propose procurement planning methods based on stochastic models which considering the multiple demand scenarios. To evaluate the performances of the proposed methods, computational experiments were carried out on the proposed methods as well as benchmarks including a method based on deterministic mathematical model and a heuristic. From the results of the computational tests, the superiorities of the proposed methods were shown.

• 한국항만학회지
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• 제13권1호
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• pp.27-40
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• 1999

This study aims to apply and examine the stochastic approach for empty container repositioning and leasing problem. For this a case study has been carried out on actual data such as various cost components and traffic flow. The results reveal that the proposed methodology produces more realistic results than the conventional deterministic approaches. It is also found that the results are significantly affected by the accuracy of demand and supply forecast.

• 대한산업공학회지
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• 제20권3호
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• pp.105-116
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• 1994

This paper presents an inventory model with partial backorders for the situation in which demand is deterministic, lead time follows normal distribution and back order ratio during the stockout period varies in proportion to the length of backorder period In this situations, an objective function is formulated to minimize a time-proportional backorder cast and a fixed penalty cost per unit lost. And then the procedure of iterative solution method for the model is developed to find optimal reorder paint and order quantity and a numerical example to illustrate the proposed method is presented.

• 한국경영과학회지
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• 제13권2호
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• pp.18-24
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• 1988

We consider sensitivity analysis sequencing problems, in which sequence of a finite set of expansion projects is sought to meet a deterministic demand projection in minimum discounted cost. In particular, by characterizing the underlying network structure, we find analytically the sensitivity range for a project cost such that the optimal sequencing policy remains unchanged for any value in the range. A numerical example is presented.

• 대한산업공학회지
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• 제4권2호
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• pp.77-81
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• 1978

The assortment problem with deterministic demand has been formulated so that a dynamic programming can be applied to find optimal production lengths that will minimize the sum of cutting losses. The original minimization problem can be reformulated as the maximization problem with a different objective function. This problem can be solved by the dynamic programming technique. A numerical example illustrates this approach. The ratio of computation amount of emumeration method to that of this dynamic programming is approximately n to 1.