• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2007년도 추계학술대회 및 정기총회
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• pp.482-487
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• 2007

As the importance of logistics is increasing, Enterprises design the supply chain(SC) network to minimize the total costs considering inventory holding cost, transportation cost and apply the efficient strategies of supply chain based on SC network Calculating the logistics costs without reflecting the logistics components like the packaging cost, transportation related cost, storage cost, loading & unloading cost, and distribution costs, the companies should have many limitation to calculate the logistics cost of real enterprise and install the SC network reducing them. Therefore, this research is aimed at establishing SC strategies which can be an efficient alternative for a decision making on supply chain, based on existing reference and current logistics networks of 'L' company in Korea and analyzing interaction effects between strategies and influence on logistics cost by these strategies. As the method of analysis, we analyze the interaction effects between strategies as well as install the optimal SC network reflecting concrete logistics components from the viewpoint of total logistics costs. we expect that analysis method of this paper would be applied various industries and used the efficient tools for the decision mating by planing and execution of the logistics budget from enterprises.

• 경영과학
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• 제25권2호
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• pp.89-109
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• 2008

As the importance of logistics is increasing, Enterprises try to design the supply chain(SC) network to minimize the total costs considering inventory holding cost, transportation cost and apply the efficient strategies of supply chain based on SC network. Despite of this efforts, Calculating the logistics costs without reflecting the real components of logistics like the packaging cost, transportation related cost, storage cost, loading & unloading cost, and distribution costs, the companies has many limitation to calculate the logistics cost of real enterprise. For overcoming such problem, this paper is aimed at establishing SC strategies which can be an efficient alternative for a decision making on supply chain, based on existing reference and current logistics networks of 'L' company in Korea. Also, we analyze the interaction effects between strategies as well as install the optimal SC network reflecting concrete logistics components from the viewpoint of total logistics costs using the simulation and statistic methods. we expect that analysis results of this paper would be applied various industries and be utilized to the efficient tools for the decision making by planing and execution of the logistics budget from enterprises.

• The Journal of Korean Physical Therapy
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• 제25권2호
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• pp.43-48
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• 2013

Purpose: The aim of this study was to demonstrate that non-participation of physical therapists on the political decision-making committee results in invasion of their interests. Methods: To demonstrate the effects, we analyzed the change of medical insurance score decided by the Health Insurance Policy Deliberation Committee between 2001 and 2012 years, focusing on medical examination as the interest of the participation group and physical therapy cost as interest of the non-participation group. Results: Total medical insurance cost increased by 23.72%, on average. Medical examination cost increased by 23.90% and 37.66% in medical examination for new and established patients, respectively. However, physical therapy cost was reduced by 5.01%. The medical examination cost for physical therapy without medical checkup increased by 2.62%. Conclusion: This study shows that the physical therapy cost, related on the interest of the non-participative group in the Health Insurance Policy Deliberation Committee, rather decreased while the total medical insurance cost increased.These findings demonstrate the invasion of the non-participative group on the Health Insurance Policy Deliberation Committee. Thus, aggressive participation in political decision-making committee is necessary in order to protect and increase rights and interests of Korean physical therapists.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.389-390
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• 2023

To improve the cost performance of construction sites, various systems and standards are constantly being developed and implemented. Although legal requirements for these system and standard improvements have been increasing, the cost efficiency performance of construction sites remains stagnant. We have digitized documents generated through construction supervision work at 39 building construction sites and proposed a model that can support decision-making in cost efficiency evaluation. This model selects key keywords that are considered to be highly related to cost efficiency by identifying the patterns and relationships of keywords through associated rule analysis and social network analysis using keywords derived from documents. In addition, it is expected to be used as a decision-making aid to determine the cost efficiency of a specific building construction site by establishing a logistic regression model using core keywords. As a systematic database of construction supervision documents and an integrated system of massive data generated by digital technology are established in the future, the accuracy and reliability of the cost efficiency evaluation model are expected to be reinforced.

• 경영과정보연구
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• 제31권4호
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• pp.309-337
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• 2012

오늘날의 시장은 기술의 진보로 인하여 과거에는 기대할 수 없던 여러 가지 기능을 제공할 수 있게 되었고 뛰어난 접근성과 반응은 고객이 원하는 때에, 원하는 물건을, 원하는 방식으로 살펴볼 수 있도록 제공해주어 고객의 욕구를 만족을 스스로 결정할 수 있는 구조를 가능하게 한다. 즉, 고객에게 스스로의 가치기준에 맞는 선택의 기회를 부여함으로서 만족을 달성하는 이러한 서비스를 TBSS (Technology-Based Self-Service)라 할 수 있다. 본 연구에서는 TBSS를 이용한 배송서비스 산업에서의 고객 만족 및 재구매의도 향상의 선행요인을 탐구하는 이론적 모형을 제안하고자 한다. 구체적으로 고객 만족과 재구매의도에 영향을 주는 지각된 가치를 '편익-비용'으로 구성하고 결과 편익과 과정 편익, 금전적 비용과 비금전적 비용의 영향력 크기를 비교하는 연구를 수행할 것이며 이를 통해 TBSS가 고객만족도 및 재구매 의도에 미치는 영향을 확인하고 유용성을 판단하는 본 연구의 결과가 고객 만족 및 재구매 의도 제고를 위한 실무적 정보를 제공하는데 도움이 되기를 기대한다.

• 산업경영시스템학회지
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• 제40권2호
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• pp.129-136
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• 2017

Among the information technology and automation that have rapidly developed in the manufacturing industries recently, tens of thousands of quality variables are estimated and categorized in database every day. The former existing statistical methods, or variable selection and interpretation by experts, place limits on proper judgment. Accordingly, various data mining methods, including decision tree analysis, have been developed in recent years. Cart and C5.0 are representative algorithms for decision tree analysis, but these algorithms have limits in defining the tolerance of continuous explanatory variables. Also, target variables are restricted by the information that indicates only the quality of the products like the rate of defective products. Therefore it is essential to develop an algorithm that improves upon Cart and C5.0 and allows access to new quality information such as loss cost. In this study, a new algorithm was developed not only to find the major variables which minimize the target variable, loss cost, but also to overcome the limits of Cart and C5.0. The new algorithm is one that defines tolerance of variables systematically by adopting 3 categories of the continuous explanatory variables. The characteristics of larger-the-better was presumed in the environment of programming R to compare the performance among the new algorithm and existing ones, and 10 simulations were performed with 1,000 data sets for each variable. The performance of the new algorithm was verified through a mean test of loss cost. As a result of the verification show, the new algorithm found that the tolerance of continuous explanatory variables lowered loss cost more than existing ones in the larger is better characteristics. In a conclusion, the new algorithm could be used to find the tolerance of continuous explanatory variables to minimize the loss in the process taking into account the loss cost of the products.

• 교육시설 논문지
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• 제25권6호
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• pp.35-44
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• 2018

The purpose of this study is to predict more accurate construction costs and to support efficient decision making in the planning and design stages of smart education facilities. The higher the error in the projected cost, the more risk a project manager takes. If the manager can predict a more accurate construction cost in the early stages of a project, he/she can secure a decision period and support a more rational decision. During the planning and design stages, there is a limited amount of variables that can be selected for the estimating model. Moreover, since the number of completed smart schools is limited, there is little data. In this study, various artificial intelligence models were used to accurately predict the construction cost in the planning and design phase with limited variables and lack of performance data. A theoretical study on an artificial neural network and deep learning was carried out. As the artificial neural network has frequent problems of overfitting, it is found that there is a problem in practical application. In order to overcome the problem, this study suggests that the improved models of Deep Neural Network and Deep Belief Network are more effective in making accurate predictions. Deep Neural Network (DNN) and Deep Belief Network (DBN) models were constructed for the prediction of construction cost. Average Error Rate and Root Mean Square Error (RMSE) were calculated to compare the error and accuracy of those models. This study proposes a cost prediction model that can be used practically in the planning and design stages.

• 산업공학
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• 제13권2호
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• pp.211-216
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• 2000

A methodology that determines the optimal shutdown time of a nuclear power plant is suggested. The shutdown time is decided considering the trade off between the cost of accident and the loss of profit due to the early shutdown. We adopt the bayesian approach in manipulating the model parameter that predicts the accidents. We build decision tree models and apply dynamic programming approach to decide whether to shutdown immediately or operate one more period. The branch parameters in decision trees are updated by bayesian approach. We apply real data to this model and provide the cost of accidents that guarantees the immediate shutdown.

• 한국정보과학회논문지:데이타베이스
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• 제34권1호
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• pp.70-83
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• 2007

대부분의 스카이라인 질의에 대한 연구는 정적인 데이타에 관하여 이루어지고 있다. 하지만, 모바일 응용환경의 발전에 따라 이동객체에 대한 연속적인 스카이라인 질의에 대한 필요성이 증대되고 있다. 연속적인 스카이라인 질의를 처리하기 위하여 4단계 스카이라인 영역 결정 기법이 최근 제안되었지만, 이 기법은 스카이라인 영역 계산 비용이 크므로 대량의 데이타 객체에 대해서는 사용되기 힘든 문제점이 있다. 이 논문은 이러한 문제를 해결하기 위하여 먼저 4단계 영역 결정 기법에 대해서 이론적으로 분석하고, 이를 바탕으로 4 단계 영역 결정 기법을 위한 점진적인 스카이라인 영역 결정 기법을 제안한다. 제안하는 기법은 거리 기반 가지치기와 영역 결정 선분의 범위 축소 기법을 이용하여 기존 기법의 스카이라인 영역결정 비용을 효율적으로 감소시킨다. 본 논문은 다양한 성능 시험을 통하여 제안된 기법의 효율성을 증명한다.

• 경영과학
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• 제32권4호
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• pp.19-28
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• 2015

This study presents a mathematical programming model to develop production planning in the manufacturing processes for photovoltaic silicon ingots and wafers. The model is formulated as a linear programming model that maximizes total growth margin, which is composed of production cost, inventory cost, shortage cost, and sales profit while considering the constraints associated with the production environments of photovoltaic materials. In order to demonstrate the utility of the model for production planning, we run operations for a planning horizon of a year for a case study. When the primary results of this mathematical programming are compared with the historical records, the model could have resulted in the considerable increase of the total growth margin by effectively reducing inventory cost if a decision maker had employed the model as a decision support system with perfect information for sales demand.