• Journal of the Korean Data and Information Science Society
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• 제15권1호
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• pp.83-94
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• 2004

In this study we analyze categorical data by means of spatial statistics and echelon analysis. To do this, we first determine the hierarchical structure of a given contingency table by using echelon dendrogram then, we detect candidates of hotspots given as the top echelon in the dendrogram. Next, we evaluate spatial scan statistics for the zones of significantly high or low rates based on the likelihood ratio. Finally, we detect hotspots of any size and shape based on spatial scan statistics.

• 한국경영과학회지
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• 제30권4호
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• pp.71-81
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• 2005

This Paper focuses on the effects of outside competition on an optimal echelon base stock level in a two stage supply chain. This is new in that we have been studying the effects of inside competition within a supply chain up to now. It is known that the optimal echelon base stock level with inside competition within a supply chain is less than the global optimal echelon base stock level without inside competition. This is due to the ' public goods ' nature of inventory. That is, more inventory is better, but one wants the other to invest more, thus resulting in under-investment. However, this phenomenon becomes weaker as outside competition increases. We show that as outside competition becomes stronger, the ' public goods ' effects decrease and the optimal echelon base stock level increases. If the level of competition is sufficiently high, the optimal echelon base stock level goes even higher than the global optimal echelon base stock level. We develop a theoretical model for the analysis and conduct a numerical analysis.

• 한국경영과학회지
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• 제29권3호
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• pp.111-127
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• 2004

We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1181-1190
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• 2006

Statistical analyses for spatial data are important features for various types of fields. Spatial data are taken at specific locations or within specific regions and their relative positions are recorded. Lattice data are synoptic observation covering an entire spatial region, like cancer rates corresponding to each county in a state. Until now, the echelon analysis has been applied only to univariate spatial data. As a result, it is impossible to detect the hotspots on the multivariate spatial data In this paper, we expand the spatial data to time series structure. And then we analyze them on the time space and detect the hotspots. Echelon dendrogram has been made by piling up each multivariate spatial data to bring time spatial data. We perform the structural analysis of temporal spatial data.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 춘계 학술발표회 논문집
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• pp.1-6
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• 2003

인공위성을 이용한 원격탐사가 일반화되어 있는 선진국의 경우 인공위성의 관측자료를 이용한 여러 가지 분야의 연구가 활발하게 이루어지고 있다. 이러한 국제적 경향은 결과적으로 원격탐사정보와 지리정보시스템 기술의 가져오게 되는 계기가 되었다. 이로 인해 환경조사 및 자원탐사, 홍수, 가뭄, 쓰레기 처리, 농업 식량예측, 사막화 해양오염 등 여러 가지 응용 분야에 유용하게 사용되고 있다. 에쉬론 해석법(Myers et. al., 1997)은 이러한 원격탐사에 의해 얻은 각종 공간 데이터 해석을 위해 개발된 것으로, 공간데이터의 위상적 구조를 계통적이고 객관적으로 발견하기 위한 해석법이다. 본 연구에서는 한국의 시${\cdot}$도별 인구 데이터에 본 해석법을 적용해 본다.

• 경영과학
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• 제28권1호
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• pp.117-127
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• 2011

In the Multi-Echelon maintenance environment, METRIC(Multi-Echelon Technique for Repairable Item Control) has been used in several different inventory level selection models, such as MOD-METRIC, Vari-METRIC, and Dyna- ETRIC. While this model's logic is easy to be implemented, a critical assumption of infinite maintenance capacity would deteriorate actual values, especially Expected Back Order(EBO)s for each item. To improve the accuracy of EBO, we develop two models using simulation and queueing theory that calculates EBO considering finite capacity. The result of our numerical example shows that the expected backorder from our model is much closer to the true value than the one from Vari-METRIC. The queueing model is preferable to the simulation model regarding the computational time.

• 자원환경지질
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• 제55권6호
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• pp.633-648
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• 2022

경기도 연천 지역에서 집중적으로 발생한 군발지진의 원인을 파악하기 위해서 중력 자료를 분석하였다. 그 결과 연천 지역에는 북서-남동 방향의 안행상(En echelon) 구조가 발달하는 것으로 나타났다. 또한, 동두천 단층 동쪽 지역은 꽃다발구조(flower structure)를 수반한 수직 지구조 운동으로 인해서 고밀도의 기반암 물질들이 부분적으로 지표 가까이 상승한 것으로 해석되었다. 동두천 단층의 파쇄대 폭은 약 200 m, 깊이는 최소 5 km이며, 밀도는 인접 지층보다 평균 약 15% 낮은 것으로 평가된다. 지하 5 km 이내에서 발생한 천발지진은 지표 가까이 관입한 고밀도 암석에 발달된 저밀도의 안행상 단층 파쇄대를 따라 집중되어 발생한 것으로 분석되는데, 이는 동두천 단층의 우수향 운동 때문에 남북 방향으로 작용한 응력이 안행상 단층을 활성화한 결과로 해석된다.

• 산업공학
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• 제13권3호
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• pp.444-454
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• 2000

Due to the improvement of modern information technologies, sharing stock information among the supply chain members is a common practice nowadays. Many companies are planning to adopt the information systems to possess the real-time shared stock information. Thus, it is needed to quantify the value of shared stock information. The purpose of this paper is to evaluate the value of the shared stock information for two-echelon distribution systems. Existing reorder policies can be classified into installation stock policies and echelon stock policies. Since installation stock policies do not utilize the shared stock information, and both classes of policies may show poor performances for distribution systems, we cannot evaluate the value of the shared stock information with the existing policies. Thus, we provide a new type of reorder policy, named order risk policy. We define the order risk using marginal analysis, and prove the optimality. Through computational experiment that compares the order risk policy with the existing policies, it is shown that a significant cost reduction is achieved with the effective utilization of the shared stock information. We also show the effect of the system characteristics on the value of the shared stock information.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.131-139
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• 2006

Statistical analyses for spatial data are important features for various types of fields. Spatial data are taken at specific locations or within specific regions and their relative positions are recorded. Lattice data are synoptic observation covering an entire spatial region, like cancer rates corresponding to each county in a state. The main purpose of this paper is to detect hotspots for the region with significantly high or low rates. Kulldorff(1997) detected hotspots based on circular spatial scan statistics. We propose a new method to find any shapes of hotspots by use of echelon analysis with spatial scan statistics.

• 경영과학
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• 제31권3호
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• pp.61-76
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• 2014

There are three methods for calculating the optimal level for spare part inventories in a MIME (Multi Indenture and Multi Echelon) system : marginal analysis, Lagrangian relaxation method, and genetic algorithm. However, their solutions are sub-optimal solutions because the MIME system is neither convex nor separable by items. To be more specific, SRUs (Shop Replaceable Units) are required to fix a defected LRU (Line Replaceable Unit) because one LRU consists of several SRUs. Therefore, the level of both SRU and LRU cannot be calculated independently. Based on the limitations of three existing methods, we proposes a improved algorithm applying marginal analysis on determining LRU stock level and genetic algorithm on determining SRU stock level. It can draw optimal combinations on LRUs through separating SRUs. More, genetic algorithm enables to extend the solution search space of a SRU which is restricted in marginal analysis applying greedy algorithm. In the numerical analysis, we compare the performance of three existing methods and the proposed algorithm. The research model guarantees better results than the existing analytical methods. More, the performance variation of the proposed method is relatively low, which means one execution is enough to get the better result.