• 산업경영시스템학회지
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• 제12권19호
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• pp.67-72
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• 1989

This paper concerns with the decision maker has the job of forecasting capital investments and operating expenses to aid the decision making in choosing and evaluating present annual and future alternatives. The cost estimating function eventually analysis, evaluates and choose the alternatives. And also, the marginal analysis performed originally from a preliminary design of some sort, and eventually plans are made to investigate investment possibilities. This paper provide the discounted net cash flows and the present, annual and future worth methods. In despite of any choice for an analytical methods, there remains the problems of predicting and assessments certain future events. Therefore, these models dealing with the optimal plant sizing, equipments replacement, and lease or buy will be discussed.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 추계학술발표회논문집(1)
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• pp.475-480
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• 1997

In order to conduct the effective integration of computer-aided conceptual design for integrated nuclear power reactor, not only is a smooth information flow required, but also decision making fur both conceptual design and construction process design must be synthesized. In addition to the aboves, the relations between the one step and another step and the methodologies to optimize the decision variables are verified, in this paper especially, that is, scaling laws and scaling criteria. In the respect with the running of the system, the integrated optimization process is proposed in which decisions concerning both conceptual design are simultaneously made. According to the proposed reactor types and power levels, an integrated optimization problems are formulated. This optimization is expressed as a multi-objective optimization problem. The algorithm for solving the problem is also presented. The proposed method is applied to designing a integrated sub-critical reactors.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2007년도 정기학술발표대회 논문집
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• pp.295-298
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• 2007

주택 재건축 정비사업의 초기단계에서의 주요문제점들은 해당분야의 전문가 부재로 인한 전문성결여에서 비롯하여 사업기간을 지연하게 되고, 또한 사업추진의 부진으로 인하여 비용 증가 등이 발생하고 있다. 이러한 내재된 정비사업의 문제 해결 방안으로서 본 연구에서는 건설사업 관리 방식의 모델 적용방안을 제안하고자 한다. 건설사업관리 방식을 적용하여 사업초기 단계에서의 사업계획 수립시 전문적인 지식을 기초로 조합원의 의견을 충분히 수렴할 수 있으며, 사업수행방식의 전문화, 초기단계에서의 합리적인 의사결정, 사업기간 단축, 비용절감, 발주자의 이익을 기여할 수 있다.

• 상하수도학회지
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• 제35권6호
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• pp.517-531
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• 2021

The water supply facilities of Korea have achieved a rapid growth, along with the other social infrastructures consisting a city, due to the phenomenon of urbanization according to economic development. Meanwhile, the level of water supply service demanded by consumer is also steadily getting higher in keeping with economic growth. However, as an adverse effect of rapid growth, the quantity of aged water supply pipes are increasing rapidly, Bursts caused by pipe aging brought about an enormous economic loss of about 6,161 billion won as of 2019. These problems are not only worsening water supply management, also increasing the regional gap in water supply services. The purpose of this study is to classify hazard evaluation indicators and to rank the water distribution network hazard by cluster using the TOPSIS method. In conclusion, in this study, the entropy-based multi-criteria decision-making methods was applied to rank the hazard management of the water distribution network, and the hazard management ranking for each cluster according to the water supply conditions of the county-level municipalities was determined according to the evaluation indicators of water outage, water leakage, and pipe aging. As such, the hazard ranking method proposed in this study can consider various factors that can impede the tap water supply service in the water distribution network from a macroscopic point of view, and it can be reflected in evaluating the degree of hazard management of the water distribution network from a preventive point of view. Also, it can be utilized in the implementation of the maintenance plan and water distribution network management project considering the equity of water supply service and the stability of service supply.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 춘계학술발표회논문집(2)
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• pp.237-243
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• 1997

The ultimate object of our study is to minimize the release of radioactive material into the environment and to maximize the treatable amount of the generated wastes. In planning the practical operation of the system, however, the operating cost, Process economics and technical flexibility must also be considered. For dealing with these multiple criteria decision making Problems, we used a foal programming which is a kind of multi-objective linear programming. This method requires the decision maker to set goals for each objective that one wishes to attain.

• 한국지능시스템학회논문지
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• 제14권7호
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• pp.934-938
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• 2004

In this paper, we introduce the seminormed fuzzy co-integral as a complementary concept of seminormed fuzzy integral, and investigate its properties. Furthermore we propose an application of this new integral for decision making problems.

• Fibers and Polymers
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• 제5권4호
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• pp.297-302
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• 2004

In many engineering applications, the final decision is based on the evaluation of a number of alternatives in terms of a number of criteria. This problem may become very intricate when the selection criteria are expressed in terms of different units or the pertinent data are difficult to be quantified. The Analytic Hierarchy Process (AHP) is an effective way in dealing with such kind of complicated problems. Cotton fiber is selected or graded, in the spinning industries, based on several quality criteria. However, the existing selection or grading method based on Fiber quality Index (FqI) is rather crude and ambiguous. This paper presents a novel approach of cotton fiber selection using the AHP methodology of Multi Criteria Decision Making.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권1호
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• pp.19-30
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• 2013

Recently, the constrained index tracking problem, in which the task of trading a set of stocks is performed so as to closely follow an index value under some constraints, has often been considered as an important application domain for control theory. Because this problem can be conveniently viewed and formulated as an optimal decision-making problem in a highly uncertain and stochastic environment, approaches based on stochastic optimal control methods are particularly pertinent. Since stochastic optimal control problems cannot be solved exactly except in very simple cases, approximations are required in most practical problems to obtain good suboptimal policies. In this paper, we present a procedure for finding a suboptimal solution to the constrained index tracking problem based on approximate dynamic programming. Illustrative simulation results show that this procedure works well when applied to a set of real financial market data.

• 한국건설관리학회논문집
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• 제9권5호
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• pp.159-167
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• 2008

건설산업관리는 건설사업의 초기부터 완성에 이르기까지 범위, 시간, 비용, 품질 등 관련 요소에 대한 통합 관리를 통해 프로젝트를 성공적으로 완수하기 위한 조직적 활동이며, 이의 궁극적 목표는 전사적 경영효율을 극대화하는 것이다. 이를 위해 관리자는 작업의 범위와 방법과 순서 및 비용과 일정을 계획, 실행, 감시 및 통제하며 그들에 수반되는 자원을 할당하고 조정한다. 자원배분은 공기 및 비용과 밀접하게 연관되고, 따라서 이들 관계에 근거한 효과적 자원배당은 하나의 의사결정문제로 모형화될 수 있다. 여기서 문제를 구성하는 의사결정기준과 대안의 성과뿐만 아니라 가중치 또한 중요한 기능을 하므로, 이들의 산정에는 일관성과 객관성이 담보되어야 한다. 본 논문은 다수의 의사결정기준하에 동시에 계획된 단일(복수) 프로젝트(현장)에 속한 활동들간에 한정된 동일 자원의 효과적 투입을 위한 우선순위를 결정하는 개념과 방법을 제시하였다. 기반 도구로 다기준 의사결정기법의 하나인 계층분석법을 활용하였으며, 세 가지 유형의 사례에 적용하여 그에 대한 타당성과 유용성을 보였다. 사례 1은 각 활동이 주공정상에 위치하며 선택기준으로 조기종료시간, 잔여후속공기, 후속활동수, 자원요구량 등을 선정하였으며, 사례 2는 경쟁 활동이 상이한 여유시간과 조기종료시간, 자원일수, 후속잔여공기, 후속활동수 등을 의사결정속성으로 선정하였다. 사례 3은 이미 수행된 4개의 농사에 대해 본 연구의 방법을 피드백하여 유용성을 검토하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권1호
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• pp.44-51
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• 2016

Recently, artificial intelligence has reached the level of top information technologies that will have significant influence over many aspects of our future lifestyles. In particular, in the fields of machine learning technologies for classification and decision-making, there have been a lot of research efforts for solving estimation and control problems that appear in the various kinds of portfolio management problems via data-driven approaches. Note that these modern data-driven approaches, which try to find solutions to the problems based on relevant empirical data rather than mathematical analyses, are useful particularly in practical application domains. In this paper, we consider some applications of modern data-driven machine learning methods for portfolio management problems. More precisely, we apply a simplified version of the sparse Gaussian process (GP) classification method for classifying users' sensitivity with respect to financial risk, and then present two portfolio management issues in which the GP application results can be useful. Experimental results show that the GP applications work well in handling simulated data sets.