• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.171-171
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• 2020

Decision making strategies should consider both adaptiveness and robustness in order to deal with two main characteristics of climate change: non-stationarity and deep uncertainty. Especially, robust strategies are different from traditional optimal strategies in the sense that they are satisfactory over a wider range of uncertainty and may act as a key when confronting climate change. In this study, a new framework named Robust Stochastic Dynamic Programming (R-SDP) is proposed, which couples previously developed robust optimization (RO) into the objective function and constraint of SDP. Two main approaches of RO, feasibility robustness and solution robustness, are considered in the optimization algorithm and consequently, three models to be tested are developed: conventional-SDP (CSDP), R-SDP-Feasibility (RSDP-F), and R-SDP-Solution (RSDP-S). The developed models were used to derive optimal monthly release rules in a single reservoir, and multiple simulations of the derived monthly policy under inflow scenarios with varying mean and standard deviations are undergone. Simulation results were then evaluated with a wide range of evaluation metrics from reliability, resiliency, vulnerability to additional robustness measures. Evaluation results were finally visualized with advanced visualization tools that are used in multi-objective robust decision making (MORDM) framework. As a result, RSDP-F and RSDP-S models yielded more risk averse, or conservative, results than the CSDP model, and a trade-off relationship between traditional and robustness metrics was discovered.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 1999년도 제15회 하계 학술발표회 논문집
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• pp.245-265
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• 1999

MAUT and AHP are widely used for quantification of subjective judgements in various fields of decision making. This study focuses on the introduction and application of MAUT/AHP method which is a hybrid of MAUT and AHP techniques in R&D project priority setting. This hybrid model can clarify each factors' contribution using MAUT method and can reduce the number of pairwise comparisons of AHP method. This study applies AMUT/AHP method to the evaluation of R&D projects in a Government - funded research institute. To evaluate R&D projects, six evaluation factors are derived. SMART(Simple MultiAttribute Rating Technique) and DVM(Difference Value Measurement ) out of many MAUT methods are used to design the utility function ad AHP is used to allocate the weights among evaluation factors. The major findings of this study can be summarized as follows. First, the SMART/AHP and the DVM/AHP have the same results with the SMART and the DVM, and they are different results with AHP. It is very hard to decide which one is better. Second, MAUT/AHP's strength is analyzed. MAUT reflects utility values of evaluators to alternatives and AHP results objective and consistent weights of factors through pariwise comparisons. Third, its possible application fields are proposed. It is applicable to subjective decision making problems with high complexity and inter-independent factors.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.496-500
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• 2015

International construction projects are inherently more risky than domestic projects with multi-dimensional uncertainties that require complementary risk management at both the country and project levels. However, despite a growing need for systematic country evaluations, most studies have focused on project-level decisions and lack country-based approaches for firms in the construction industry. Accordingly, this study suggests data-driven approaches for evaluating countries using two quantitative models. The first is a two-stage country segmentation model that not only screens negative countries based on country attractiveness (macro-segmentation) but also identifies promising countries based on the level of past project performance in a given country (micro-segmentation). The second is a multi-criteria country segmentation model that combines a firm's business objective with the country evaluation process based on Kraljic's matrix and fuzzy preference relations (FPR). These models utilize not only secondary data from internationally reputable institutions but also performance data on Korean firms from 1990 to 2014 to evaluate 29 countries. The proposed approaches enable firms to enhance their decision-making capacity for evaluating and selecting countries at the early stage of corporate strategy development.

• 기술혁신학회지
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• 제5권1호
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• pp.90-109
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• 2002

The national nuclear R&D projects have been implemented for the purpose of supply of nuclear power which was proved to be safety and stability. Evaluating the national nuclear R&D projects has critical importance in nu-clear energy management aspect. This paper employs multi-attribute utility analysis as a basis for obtaining an evaluation index to assess the national nuclear R&D projects using a specific case study of Korea. To structure and quantify basic values for the evaluation, we elicited important attributes, then refined and structured them into a hierarchy. A multi-attribute index is constructed as a multi-attribute utility function, based on value judgments provided by a group of technical experts, policy makers, and faculties. As a result, the objective of attainment of a proposed object is given the highest priority, followed by appropriateness of project and research strategy, utilization of research output, within attribute ranges defined for the attributes. We found that the work and results of this study can provide valuable insights and decision opportunities for virtually all major decision making in evaluation of the national nuclear R&D projects in Korea.

• 산업경영시스템학회지
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• 제34권2호
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• pp.112-120
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• 2011

The early phase of design intrinsically contains multiple sources of uncertainty in describing design, and nevertheless the decision-making process at this phase exerts a critical effect upon drawing a successful design. This paper proposes a set-based design approach for multi-objective design problem under uncertainty. The proposed design approach consists of four design processes including set representation, set propagation, set modification, and set narrowing. This approach enables the flexible and robust design while incorporating designer's preference structure. In contrast to existing optimization techniques, this approach generates a ranged set of design solutions that satisfy changing sets of performance requirements.

• Structural Engineering and Mechanics
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• 제71권2호
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• pp.139-151
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• 2019

In a project schedule, it is possible to reduce the time required to complete a project by allocating extra resources for critical activities. However, accelerating a project causes additional expense. This issue is addressed by finding optimal set of time-cost alternatives and is known as the time-cost trade-off problem in the literature. The aim of this study is to identify the optimal set of time-cost alternatives using a multiobjective teaching-learning-based optimization (TLBO) algorithm integrated with the non-dominated sorting concept and is applied to successfully optimize the projects ranging from a small to medium large projects. Numerical simulations indicate that the utilized model searches and identifies optimal / near optimal trade-offs between project time and cost in construction engineering and management. Therefore, it is concluded that the developed TLBO-based multiobjective approach offers satisfactorily solutions for time-cost trade-off optimization problems.

• 품질경영학회지
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• 제20권1호
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• pp.126-135
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• 1992

The decision making process for production planning in FMS usually involves multiple conflicting objectives and criteria. This study consists of prescreening and analytical phase. In the prescreening phase, criteria are used to reduce the set of alternative system configuration down to a small number of candidates. After this phase, a multiobjected programming model is formulated for each remainning configuration.

• 산업경영시스템학회지
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• 제28권4호
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• pp.94-101
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• 2005

This paper presents a data-mining aided heuristic algorithm development. The developed algorithm includes three steps. The steps are a uniform selection, development of feature functions and clustering, and a decision tree making. The developed algorithm is employed in designing an optimal multi-station fixture layout. The objective is to minimize the sensitivity function subject to geometric constraints. Its benefit is presented by a comparison with currently available optimization methods.

• Journal of Information Science Theory and Practice
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• 제7권4호
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• pp.56-64
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• 2019

Planting intercropping in rubber plantations is another alternative for generating more income for farmers. However, farmers still lack the knowledge of choosing plants. In addition, information for decision making comes from many sources and is knowledge accumulated by the expert. Therefore, this research aims to create a decision support system for growing rubber trees for individual farmers. It aims to get the highest income and the lowest cost by using semantic web technology so that farmers can access knowledge at all times and reduce the risk of growing crops, and also support the decision supporting system (DSS) to be more intelligent. The integrated intercropping ontology and rule are a part of the decision-making process for selecting plants that is suitable for individual rubber plots. A list of suitable plants is important for decision variables in the allocation of planting areas for each type of plant for multiple purposes. This article presents designing and developing the intercropping ontology for DSS which defines a class based on the principle of intercropping in rubber plantations. It is grouped according to the characteristics and condition of the area of the farmer as a concept of the rubber plantation. It consists of the age of rubber tree, spacing between rows of rubber trees, and water sources for use in agriculture and soil group, including slope, drainage, depth of soil, etc. The use of ontology for recommended plants suitable for individual farmers makes a contribution to the knowledge management field. Besides being useful in DSS by offering options with accuracy, it also reduces the complexity of the problem by reducing decision variables and condition variables in the multi-objective optimization model of DSS.

• Spatial Information Research
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• 제11권1호
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• pp.1-12
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• 2003

현재 개별공시지가를 산정하는 과정에서 비교표준지를 선정하는 작업은 지적 담당공무원의 수작업에 의하여 이루어지고 있다. 한정된 시간에 많은 개별필지의 비교표준지 선정 작업으로 인하여, 객관적이고 합리적으로 비교표준지를 선정하기에는 어려움이 있다. 또한 현재 NGIS(국가지리정보체계)나 US(도시정보체계)등에 의한 국가적인 지형정보체계 구축사업이 급속도로 진전되고 있다. 이에 따라 토지의 가치평가의 한 분야인 개별토지의 지가산정 작업도 최신의 자동화된 방법을 적용할 필요성이 증대되고 있다. 따라서, 본 연구에서는 공간 다기준 의사결정 방법 중에서 AHP, Concordance, Ideal Point 방법을 이용하며 비교표준지를 자동으로 선정하였다. 세 가지 방법을 적용하여 나온 결과를 현재의 비교표준지와 비교하여본 결과, Ai)p 방법이 가장 현실성이 있는 대안으로 선정되었다. 본 연구의 결과와 현재 사용중인 비교표준지를 연계하여 이용한다면 좀더 객관적이고 합리적인 비교표준지 선정이 이루어질 것으로 기대한다.