• 제목/요약/키워드: multi-linear model

검색결과 724건 처리시간 0.034초

컨텍스트 의존 DEA를 활용한 다기준 ABC 재고 분류 방법 (Multi -Criteria ABC Inventory Classification Using Context-Dependent DEA)

  • 박재훈;임성묵;배혜림
    • 산업경영시스템학회지
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    • 제33권4호
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    • pp.69-78
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    • 2010
  • Multi-criteria ABC inventory classification is one of the most widely employed techniques for efficient inventory control, and it considers more than one criterion for categorizing inventory items into groups of different importance. Recently, Ramanathan (2006) proposed a weighted linear optimization (WLO) model for the problem of multi-criteria ABC inventory classification. The WLO model generates a set of criteria weights for each item and assigns a normalized score to each item for ABC analysis. Although the WLO model is considered to have many advantages, it has a limitation that many items can share the same optimal efficiency score. This limitation can hinder a precise classification of inventory items. To overcome this deficiency, we propose a context-dependent DEA based method for multi-criteria ABC inventory classification problems. In the proposed model, items are first stratified into several efficiency levels, and then the relative attractiveness of each item is measured with respect to less efficient ones. Based on this attractiveness measure, items can be further discriminated in terms of their importance. By a comparative study between the proposed model and the WLO model, we argue that the proposed model can provide a more reasonable and accurate classification of inventory items.

다단계제조공정의 품질개선을 위한 종속대안선택 근사해법 (Heuristic Algorithm for Selecting Mutually Dependent Qualify Improvement Alternatives of Multi-Stage Manufacturing Process)

  • 조남호
    • 산업경영시스템학회지
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    • 제11권18호
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    • pp.7-15
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    • 1988
  • This study is concerned with selecting mutually dependent quality improvement alternatives with resource constraints. These qualify improvement alternatives art different fro the tradition at alternatives which are independent from each other. In other words, selection of any improvement alternative requires other related specific improvement. Also the overall product quality in a multi stage manufacturing process is characterized by a complex multiplication method rather than a simple addition method which dose not allow to solve a linear knapsack problem despite its popularity in the traditional study. This study suggests a non-linear integer programming model for selecting mutually dependent quality improvement alternatives in multi-stage manufacturing process. In order to apply the model to selecting alternatives. This study also suggests a heuristic mode1 based on a dynamic programming model which is more practical than the non-linear integer programming model. The logic of the heuristic model enables 1) to estimate improvement effectiveness values on all improvement alternatives specifically defined for this study. 2) to arrange the effectiveness values in a descending order, and 3) to select the best one among the alternatives based on their forward and backward linkage relationships. This process repeats to selects other best alternatives within the resource constraints. This process is presented in a Computer programming in Appendix A. Alsc a numerical example of model application is presented in Chapter 4.

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구동력을 고려한 자전거 안정성에 관한 연구 (Study of Effect of Tractive Force on Bicycle Self-Stability)

  • 서병일
    • 대한기계학회논문집A
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    • 제36권11호
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    • pp.1319-1326
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    • 2012
  • 본 논문은 구동력이 자전거의 self-stability 에 미치는 영향을 해석한다. 운전자의 제어를 고려하지 않는 자전거의 self-stability 는 자전거의 선형 모델로부터 고유치를 구하여 해석 할 수 있다. 전륜과 후륜에 작용하는 자전거 구동력을 고려한 선형모델을 개발하고 이로부터 구동력이 안정성에 미치는 영향을 규명하였다. 선형모델의 결과가 다물체 동역학 모델의 시뮬레이션을 통한 비선형 자전거 모델에서도 같은 결과를 보임을 확인하였다.

Multi-scale heat conduction models with improved equivalent thermal conductivity of TRISO fuel particles for FCM fuel

  • Mouhao Wang;Shanshan Bu;Bing Zhou;Zhenzhong Li;Deqi Chen
    • Nuclear Engineering and Technology
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    • 제55권3호
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    • pp.1140-1151
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    • 2023
  • Fully Ceramic Microencapsulated (FCM) fuel is emerging advanced fuel material for the future nuclear reactors. The fuel pellet in the FCM fuel is composed of matrix and a large number of TRistructural-ISOtopic (TRISO) fuel particles which are randomly dispersed in the SiC matrix. The minimum layer thickness in a TRISO fuel particle is on the order of 10-5 m, and the length of the FCM pellet is on the order of 10-2 m. Hence, the heat transfer in the FCM pellet is a multi-scale phenomenon. In this study, three multi-scale heat conduction models including the Multi-region Layered (ML) model, Multi-region Non-layered (MN) model and Homogeneous model for FCM pellet were constructed. In the ML model, the random distributed TRISO fuel particles and coating layers are completely built. While the TRISO fuel particles with coating layers are homogenized in the MN model and the whole fuel pellet is taken as the homogenous material in the Homogeneous model. Taking the results by the ML model as the benchmark, the abilities of the MN model and Homogenous model to predict the maximum and average temperature were discussed. It was found that the MN model and the Homogenous model greatly underestimate the temperature of TRISO fuel particles. The reason is mainly that the conventional equivalent thermal conductivity (ETC) models do not take the internal heat source into account and are not suitable for the TRISO fuel particle. Then the improved ETCs considering internal heat source were derived. With the improved ETCs, the MN model is able to capture the peak temperature as well as the average temperature at a wide range of the linear powers (165 W/cm~ 415 W/cm) and the packing fractions (20%-50%). With the improved ETCs, the Homogenous model is better to predict the average temperature at different linear powers and packing fractions, and able to predict the peak temperature at high packing fractions (45%-50%).

다중 퍼지 추론 모델에 의한 비선형 시스템의 최적 동정 (The optimal identification of nonlinear systems by means of Multi-Fuzzy Inference model)

  • 정회열;오성권
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 D
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    • pp.2669-2671
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    • 2001
  • In this paper, we propose design a Multi-Fuzzy Inference model structure. In order to determine structure of the proposed Multi-Fuzzy Inference model, HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy are identified by genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy model and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

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HCM 클러스터링과 유전자 알고리즘을 이용한 다중 퍼지 모델 동정 (Identification of Multi-Fuzzy Model by means of HCM Clustering and Genetic Algorithms)

  • 박호성;오성권
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.370-370
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    • 2000
  • In this paper, we design a Multi-Fuzzy model by means of HCM clustering and genetic algorithms for a nonlinear system. In order to determine structure of the proposed Multi-Fuzzy model, HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy ate identified by genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy mode] and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

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유전자알고리즘 기반 복수 분류모형 통합에 의한 캐피탈고객의 신용 스코어링 모형 (A credit scoring model of a capital company's customers using genetic algorithm based integration of multiple classifiers)

  • 김갑식
    • 한국컴퓨터정보학회논문지
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    • 제10권6호
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    • pp.279-286
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    • 2005
  • 본 연구에서는 캐피탈시장에서의 고객신용예측을 위한 모형으로 여러 가지 인공신경망(Neural Network) 모형들을 유전자 알고리즘(Genetic Algorithm)을 이용하여 통합한 신용예측모형을 제안하였다. 10개의 학습된 인공신경망 모형들을 유전자알고리즘을 이용하여 종류별로 통합하여 MLP (Multi-Layered Perceptron), Linear, RBF(Radial Basis Function) 세 가지의 대표모델을 얻고 이를 다시 하나의 인공신경망 모델로 통합하였다. 이를 통합되기 이전의 각각의 인공신경망 모형들과 성능을 비교, 분석하여 본 연구에서 제안한 통합모형의 유효성과 통합방법의 타당성을 제시하였다.

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농업용 저수지의 다목적 이용을 위한 용수의 적정배분 (Optimized Allocation of Water for the Multi-Purpose Use in Agricultural Reservoirs)

  • 신일선;권순국
    • 한국농공학회지
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    • 제29권3호
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    • pp.125-137
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    • 1987
  • The purpose of this paper is to examine some difficulties in water management of agricultural reservoirs in Korea, for there are approximately more than 15,000 reservoirs which are now being utilized for the purpose of irrigation, along with the much amount of expenses and labors to be invested against droughts and floods periodically occurred. Recently, the effective use of water resources in the agricultural reservoirs with a single purpose, is becomming multiple according to the alterable environment of water use. Therefore, the task to allocate agricultural water rationally and economically must be solved for the multiple use of agricultural reservoirs. On the basis of the above statement, this study aims at suggesting the rational method of water management by introducing an optimal technique to allocate the water in an existing agricultural reservoir rationally, for the sake of maximizing the economic effect. To achieve this objective, a reservoir, called "0-Bongje" as a sample of the case study, is selected for an agricultural water development proiect of medium scale. As a model for the optimum allocation of water in the multi-purpose use of reservoirs a linear programming model is developed and analyzed. As a result, findings of the study are as follows : First, a linear programing model is developed for the optimum allocation of water in the multi-purpose use of agricultural reservoirs. By adopting the model in the case of reservoir called "O-Bongje," the optimum solution for such various objects as irrigation area, the amount of domestic water supply, the size of power generation, and the size of reservoir storage, etc., can be obtained. Second, by comparing the net benefits in each object under the changing condition of inflow into the reservoir, the factors which can most affect the yearly total net benefit can be drawn, and they are in the order of the amount of domestic water supply, irrigation area, and power generation. Third, the sensitivity analysis for the decision variable of irrigation which may have a first priority among the objects indicate that the effective method of water management can be rapidly suggested in accordance with a condition under the decreasing area of irrigation. Fourth, in the case of decision making on the water allocation policy in an existing multi-purpose reservoir, the rapid comparison of numerous alternatives can be possible by adopting the linear programming model. Besides, as the resources can be analyed in connection with various activities, it can be concluded that the linear programing model developed in this study is more quantitative than the traditional methods of analysis. Fifth, all the possible constraint equations, in using a linear programming model for adopting a water allocation problem in the agricultural reservoirs, are presented, and the method of analysis is also suggested in this study. Finally, as the linear programming model in this study is found comprehensive, the model can be adopted in any different kind of conditions of agricultural reservoirs for the purpose of analyzing optimum water allocation, if the economic and technical coefficients are known, and the decision variable is changed in accordance with the changing condition of irrigation area.

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클러스터링 기법과 유전자 알고리즘에 의한 다중 퍼지 모델으 동정 (The Identification of Multi-Fuzzy Model by means of HCM and Genetic Algorithms)

  • 박병준;이수구;오성권;김현기
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 D
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    • pp.3007-3009
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    • 2000
  • In this paper, we design a Multi-Fuzzy model by means of clustering method and genetic algorithms for a nonlinear system. In order to determine structure of the proposed Multi-Fuzzy model. HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy are identified by genetic algorithms. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy model and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

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점탄성 감쇠기의 비선형거동을 고려한 선형모델 해석 (Linear Modeling of Viscoelastic Dampers Considering Nonlinear Dynamic Behavior)

  • 김진구;권영집;민경원
    • 한국구조물진단유지관리공학회 논문집
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    • 제6권1호
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    • pp.171-177
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    • 2002
  • The viscoelastic dampers are considered to be one of the most efficient means of upgrading existing structures against seismic loads. Generally in the dynamic analysis of a structure with added viscoelastic dampers the internal forces of the dampers are represented by constants that are linearly proportional to displacement and velocity. The purpose of this study is to verify the validity of the linear Kelvin model by comparing the results from the linear analysis with those obtained from the more rigorous nonlinear model such as fractional derivative model. According to the results the structural responses of 1-DOF structure obtained using the linear model are very close to those obtained from nonlinear model. However for multi-D0F structure the difference between the results from both models is enlarged as a results of the assumptions associated with the linear modeling of the viscoelastic dampers.