• 한국경영과학회지
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• 제29권3호
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• pp.63-78
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• 2004

This paper deals with a supplier-managed inventory(SMI) control for a two-echelon supply chain model with a service facility and a single supplier. The service facility is allocated to customers and provides a service using items of inventory that are purchased from the supplier, Assuming that the supplier knows the information of customer queue length as well as inventory position in the service facility at the time when it makes a replenishment decision, we identify an optimal replenishment policy which minimizes the total supply chain costs by reflecting these information into the replenishment decision. Numerical analysis demonstrates that the SMI strategy can be more cost-effective when the information of both customer queue length and inventory position is shared than when the information of inventory position only is shared.

• 대한산업공학회지
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• 제41권3호
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• pp.259-266
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• 2015

Among many energy resources, natural gas has recently received a remarkable amount of attention, particularly from the electrical generation industry. This is in part due to increasing shale gas production, providing an environment-friendly fossil fuel, and high risk of nuclear power. Because South Korea, the world's second largest LNG importing nation after Japan, has no international natural gas pipelines and relies on imports in the form of LNG, the natural gas has been traditionally procured by long term LNG contracts at relatively high price. Thus, there is a need of developing an Asian LNG trading hub, where LNG can be traded at more competitive spot prices. In a natural gas spot market, the amount of natural gas to be bought should be carefully determined considering a limited storage capacity and future pricing dynamics. In this work, the problem to find the optimal amount of natural gas in a spot market is formulated as a Markov decision process (MDP) in risk neutral environment and the optimal base stock policy which depends on a stage and price is established. Taking into account price and demand uncertainties, the basestock target levels are simply approximated from dynamic programming. The simulation results show that the basestock policy can be one of effective ways for procurement of LNG in a spot market.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2007년도 한국컴퓨터종합학술대회논문집 Vol.34 No.1 (C)
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• pp.319-323
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• 2007

실세계의 여러 문제들은 마르코프 결정 문제(Markov decision problem, MDP)로 표현될 수 있고, 이 MDP는 모델이 알려진 경우에는 평가치 반복(value iteration) 이나 모델이 알려지지 않은 경우에도 강화 학습(reinforcement learning) 알고리즘 등을 사용하여 풀 수 있다. 하지만 이들 알고리즘들은 시간 복잡도가 높아 크기가 큰 실세계 문제에 적용하기 쉽지 않아, MDP를 계층적으로 분할하거나, 여러 단계를 묶어서 수행하는 등의 시간적 추상화(temporal abstraction) 방법이 제안되어 왔다. 이러한 시간적 추상화 방법들의 문제점으로는 시간적 추상화의 디자인에 따라 MDP의 풀이 성능이 크게 달라질 수 있으며, 많은 경우 사용자가 이 디자인을 직접 제공해야 한다는 것들이 있다. 최근 사용자의 간섭이 필요 없이 자동적으로 시간적 추상화를 만드는 방법들이 제안된 바 있으나, 이들 방법들 역시 결과물에 대한 이론적인 성능 보장(performance guarantee)은 제공하지 못하고 있다. 본 연구에서는 이러한 문제점을 해결하기 위해 MDP의 구조와 그 풀이 성능을 연관짓는 복잡도 척도에 대해 살펴본다. 이를 위해 MDP로부터 얻은 상태 경로 그래프(state trajectory graph)의 위상적 성질들을 여러 네트워크 척도(network measurements) 들을 이용하여 측정하고, 이와 MDP의 풀이 성능과의 관계를 다양한 상황에 대해 실험적, 이론적으로 분석해 보았다.

• 한국통신학회논문지
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• 제28권5C호
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• pp.506-513
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• 2003

Most existing space-time coding (STC) schemes have been developed for flat fading channels. To obtain antenna diversity gain, they rely on channel state information (CSI) required at the receiver through channel estimation techniques. This paper proposes a new decision feedback decoding scheme for Alamouti-based space-time block coding (STBC) transmission over time-selective fading channels. In wireless channels, time-selective fading effects arise mainly due to Doppler shift and carrier frequency offset, Modelling the time-selective fading channels as the first-order Gauss-Markov processes, we use recursive algorithms such as Kalman filtering, LMS and RLS algorithms for channel tracking. The proposed scheme consists of the symbol decoding stage and channel tracking algorithms. Computer simulations confirm that the proposed scheme shows the better performance and robustness to time-selectivity.

• 한국항공우주학회지
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• 제50권4호
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• pp.287-295
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• 2022

저고도 궤적의 장사정포 위협이 대두됨에 따라 이를 방어할 요격 시스템의 개발이 시작될 예정이다. 이러한 장사정포의 공격을 방어하는 문제는 전형적인 동적 무기 표적 할당 문제다. 동적 무기 표적 할당 문제에서는 한 시점에서의 의사결정 결과가 이후 시점의 의사결정 과정에 영향을 주며, 이는 마코브 의사결정 모형의 특징이기도 하다. 장사정포의 공격을 방어하기 위한 의사결정 과정에 허용되는 시간은 공격자와 방어자의 거리를 고려할 때 저고도 궤적의 동시 다발성 발사체에 대한 대응은 수 초 이내에 결정되어야 하나, 짧은 시간 내에 마코브 의사결정 과정으로 최적해를 구하는 것은 불가능하다. 본 논문에서는 장사정포 공격을 방어하는 동적 무기 표적 할당 문제를 마코브 의사결정 문제로 나타내고, 3가지 시나리오를 작성한 후 근사적 동적계획 방법을 적용하여 요격이 가능 시간 안에 해의 도출이 가능한지를 시뮬레이션을 통하여 확인하였다. 도출된 해의 품질을 검증하기 위하여 각 시나리오에 대하여 근사적 동적계획을 적용한 결과와 Shoot-Shoot-Look 방법을 적용한 결과를 비교하였다. 시뮬레이션 결과, 장사정포의 방어 시나리오에 대하여 근사적 동적계획의 결과가 Shoot-Shoot-Look 방법을 이용한 결과보다 우수함을 보였다.

• 산업경영시스템학회지
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• 제45권4호
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• pp.42-52
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• 2022

North Korea continues to upgrade and display its long-range rocket launchers to emphasize its military strength. Recently Republic of Korea kicked off the development of anti-artillery interception system similar to Israel's "Iron Dome", designed to protect against North Korea's arsenal of long-range rockets. The system may not work smoothly without the function assigning interceptors to incoming various-caliber artillery rockets. We view the assignment task as a dynamic weapon target assignment (DWTA) problem. DWTA is a multistage decision process in which decision in a stage affects decision processes and its results in the subsequent stages. We represent the DWTA problem as a Markov decision process (MDP). Distance from Seoul to North Korea's multiple rocket launchers positioned near the border, limits the processing time of the model solver within only a few second. It is impossible to compute the exact optimal solution within the allowed time interval due to the curse of dimensionality inherently in MDP model of practical DWTA problem. We apply two reinforcement-based algorithms to get the approximate solution of the MDP model within the time limit. To check the quality of the approximate solution, we adopt Shoot-Shoot-Look(SSL) policy as a baseline. Simulation results showed that both algorithms provide better solution than the solution from the baseline strategy.

• 한국경영과학회지
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• 제35권1호
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• pp.83-95
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• 2010

This paper considers a firm that operates make-to-stock and make-to-order facilities in successive stages. The make-to-stock facility produces components which are consumed by the external market demand as well as the internal make-to-order operation. The make-to-order facility processes customer orders with the option of acceptance or rejection. In this paper, we address the problem of coordinating how to allocate the capacity of the make-to-stock facility to internal and external demands and how to control incoming customer orders at the make-to-order facility so as to maximize the firm's profit subject to the system costs. To deal with this issue, we formulate the problem as a Markov decision process and characterize the structure of the optimal inventory allocation and customer order control. In a numerical experiment, we compare the performance of the optimal policy to the heuristic with static inventory allocation and admission control under different operating conditions of the system.

• International Journal of Contents
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• 제12권4호
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• pp.31-44
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• 2016

Knowledge creation and management are regarded as critical success factors for an organization's survival in the knowledge era. As a process of knowledge acquisition and sharing, organizational learning mechanisms (OLMs) guide the learning function of organizations represented by its different learning activities. We examined a variety of learning processes that constitute OLMs. In this study, we aimed to capture the process and framework of OLMs and knowledge sharing and acquisition. Factors facilitating OLMs were investigated at three levels: individual, group, and organizational. The concept of an OLM has received some attention in the field of organizational learning, however, the relationship among the factors generating OLMs has not been empirically tested. As part of the ongoing discussion, we attempted a systemic approach for OLMs. OLMs can be represented by factors that are inherent to the organization's system; therefore, prior to empirically testing the OLM generating factor(s), evaluation of its organizational integration is required to determine effective treatment of each factor. Thus, we developed a framework to manage knowledge and proposed a method to numerically evaluate factors influencing the OLMs. Specifically, composite importance (CI) of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was applied to explore the interaction effect of these factors based on systemic approach. The augmented matrix thus generated is expected to serve as a stochastic matrix of an absorbing Markov chain.

• 한국정보전자통신기술학회논문지
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• 제10권1호
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• pp.85-94
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• 2017

본 논문에서는 동물소리 인식시스템을 위하여 최대 빈도모델 탐색 알고리즘을 고안하고 이를 이용한 소리모델을 생성하는 방법을 제안하였다. 소리모델 생성 방법은 동물종의 소리 데이터로부터 학습과정, 비터비 탐색과정 및 최대 빈도모델 탐색과정을 반복하면서 HMM(Hidden Makcov Model)모델의 구조(상태의 수와 GMM의 수)를 탐색하여 최적의 인식률을 갖는 모델집합이 생성하는 방법이다. 최대 빈도모델 탐색 알고리즘은 입력 소리 데이터를 비터비(Viterbi) 알고리즘으로 탐색하여 모델리스트를 생성하고 이 리스트 중에서 최대 빈도수의 모델을 탐색하여 최종 인식결과로 결정하는 방법이다. 알고리즘에서 소리특징으로 MFCC(Mel Frequency Cepstral Coefficient), 모델형식으로 HMM을 이용하고 C# 프로그래밍언어로 구현 하였다. 알고리즘의 성능을 평가하기 위하여 27종의 동물소리를 선정하고 실험을 하였으며 27개의 HMM 모델집합이 97.29 퍼센트의 인식률로 생성됨을 확인하였다.