• Industrial Engineering and Management Systems
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• 제12권3호
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• pp.254-263
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• 2013

Disassembly of discarded products takes place in the process of remanufacturing, recycling, and disposal. The disassembly lines have been taken as available choice for automated disassembly; therefore, it has become essential that it be designed and balanced to work efficiently. The multi-objective disassembly line balancing problem seeks to find a disassembly sequence which provides a feasible disassembly sequence, minimizes the number of workstations and idle time, and balances the line for the disassembly of post consumed product by considering the environment effects. This paper proposes a multi-criteria decision making technique based heuristic for assigning the disassembly tasks to the workstations. In the proposed heuristic, the PROMETHEE method is used for prioritizing the tasks to be assigned. The tasks are assigned to the disassembly workstations according to their priority rank and precedence relations. The proposed heuristic is illustrated with an example, and the results show that substantial improvement in the performance is achieved compared with other heuristics.

• 한국수자원학회논문집
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• 제47권7호
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• pp.573-585
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• 2014

본 연구에서는 물환경 정책 및 계획의 추진과정에서 발생할 수 있는 갈등을 풀어나갈 수 있도록 다양한 이해당사자들의 참여, 투명한 정보공개, 객관적 의사결정과정, 개별 이해당사자들의 의견 반영 등 합의형성을 위한방법론 또는 도구로서 합의형성 지원시스템을 제안하였다. 개발된 합의형성 지원시스템은 물환경 문제에 대하여 영향력을 가진 특정 집단이 해결안을 제시하여 강요하거나 설득하는 구조 대신에 다양한 이해당사자의 참여를 바탕으로 한 공동적 문제해결 방식을 기반으로 하였다. 즉, 합의에 도달하기 위해서 협상 및 조정과 같은 상호작용을 통해 이해관계를 조정하여 이해당사자들 스스로 갈등을 해결할 수 있는 환경을 제공한다는 것이다. 개발된 합의형성 지원시스템의 적용성을 검증하기 위하여 한탄강댐 건설 사례에 대한 제한적인 롤플레잉 모의실험을 수행하였다. 본 연구는 합의형성 지원시스템의 적용을 통해 정부가 지역사회나 NGO 등과 공론의 장을 마련하여 적극적으로 합의형성을 이룰 수 있도록 노력한다면 협상의 효과를 한층 높일 수 있음을 확인할 수 있었다.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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• pp.53-62
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• 2020

The COVID 19 pandemic has led to a new global recession and is still causing a lot of issues because of the delays in the employment of people. This scenario has severe consequences for many countries' labor markets in the world. This problem's complexity and importance requires an integrated method of subjective and objective evaluation rather than intuitive decisions. This research aims to investigate sustainable indexes for assessing the unemployment problem by using a Multi-Criteria Decision-Making Model (MCDM). Grey theory and Decision Making Trial and Evaluation Laboratory (GDEMATEL) are deployed to transform the experts' opinions into quantitative data. The analysis based on 20 crucial criteria is employed to determine the weights of sustainability of unemployment problems. The results revealed that the top ten of determinants are Economic growth, Industrialization, Foreign direct investment, Real GDP per capita, Education level, Trade Openness, Capacity Utilization Rate, Urbanization, Employability skills, Education system expansion, which have the most significant effects on the unemployment rate under COVID 19 impacts. Furthermore, GDEMATEL could effectively assess the sustainable indicators for unemployment problems in "deep and wide" aspects. The study proposes the Grey MCDM model, contributes to the literature, provides future research directions, and helps policymakers and researchers achieve the best solutions to the unemployment problems under "economic shocks."

• Structural Monitoring and Maintenance
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• 제1권3호
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• pp.249-271
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• 2014

This paper presents a unique study of Structural Health Monitoring (SHM) for the maintenance decision making about a real life movable bridge. The mechanical components of movable bridges are maintained on a scheduled basis. However, it is desired to have a condition-based maintenance by taking advantage of SHM. The main objective is to track the operation of a gearbox and a rack-pinion/open gear assembly, which are critical parts of bascule type movable bridges. Maintenance needs that may lead to major damage to these components needs to be identified and diagnosed timely since an early detection of faults may help avoid unexpected bridge closures or costly repairs. The fault prediction of the gearbox and rack-pinion/open gear is carried out using two types of Artificial Neural Networks (ANNs): 1) Multi-Layer Perceptron Neural Networks (MLP-NNs) and 2) Fuzzy Neural Networks (FNNs). Monitoring data is collected during regular opening and closing of the bridge as well as during artificially induced reversible damage conditions. Several statistical parameters are extracted from the time-domain vibration signals as characteristic features to be fed to the ANNs for constructing the MLP-NNs and FNNs independently. The required training and testing sets are obtained by processing the acceleration data for both damaged and undamaged condition of the aforementioned mechanical components. The performances of the developed ANNs are first evaluated using unseen test sets. Second, the selected networks are used for long-term condition evaluation of the rack-pinion/open gear of the movable bridge. It is shown that the vibration monitoring data with selected statistical parameters and particular network architectures give successful results to predict the undamaged and damaged condition of the bridge. It is also observed that the MLP-NNs performed better than the FNNs in the presented case. The successful results indicate that ANNs are promising tools for maintenance monitoring of movable bridge components and it is also shown that the ANN results can be employed in simple approach for day-to-day operation and maintenance of movable bridges.

• 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.

• 디자인학연구
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• 제20권3호
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• pp.61-72
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• 2007

1960년대 MIT에서 제작된 최초의 게임 Space War를 시작으로 짧은 기간 동안 게임산업은 급속도로 성장하고 방대해지면서 최근 발표된 게임들은 총합적 디자인의 결정체라고 봐도 무방하리만큼 콘텐츠를 이루는 구성요소가 무수히 많아졌다. 결국 게임을 개발함에 있어서 고려해야할 요소도 기하급수적으로 증가하여, 예산 및 인력, 시간투입 등에 대한 계획도 매우 복잡해질 수밖에 없다. 그러므로 성공적인 게임개발을 위해서는 게임을 구성하는 요소를 추출하고 각 요소별 중요도를 산출하여, 향후 개발되는 게임을 사전에 평가할 수 있는 방법이 무엇보다 절실하다. 이러한 기획은 진행과정에서 무수한 의사결정을 요구하게 되고, 의사결정 작업은 다수인자에 대한 문제, 요소들을 정량화시키기 어려운 불확실성의 문제, 결과가 지향하는 복잡한 다목적의 문제, 다수의 의사결정간의 혼선, 의사결정과정에 이르는 다단계의 우선순위 결정문제 등으로 인한 많은 어려움이 있다. 본 연구는 이러한 문제들을 총합적으로 해결하며, 불확실한 데이터를 정량화시켜 논리적이고 합리적인 대안을 제시할 수 있도록 계층화의사결정법을 제시하고자 하며, 현재 게임시장을 주도하고 있는 FPS게임을 대상으로 분석을 시도하였다. AHP분석에서 가장 중요한 것은 분석하고자 하는 대상의 요소들을 객관적으로 정확하게 분류하고 이를 계층화시키는 것과 요소간의 쌍대비교를 통한 중요도 추출이다. 본 연구는 이러한 요소추출과 요소간 중요도 산출 및 대안의 선정 2부분으로 구성되며, 그 중에서 본 논문은 델파이기법에 의한 FPS게임의 객관적 요소추출 및 계층화를 중심으로 하고 있다.

• Journal of information and communication convergence engineering
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• 제20권1호
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• 품질경영학회지
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• 제47권1호
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• pp.163-186
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• 2019

Purpose: The purpose of this study was to present a methodology for assessing the efficiency of supply chain quality management considering characteristics of defense industries to provide academic and policy implications for strengthening quality competitiveness of military supplies. Methods: Using the defense industry's empirical data, conduct an efficiency evaluation by utilizing a multi-stage DEA/Entropy Model for defense industries subject to the quality level survey of military goods manufacturers in 2017. Results: The results of this study are as follows; the first step of the multi-stage DEA model, Quality Management Performance Efficiency Analysis, shows that the CCR model and the BCC model are more efficient than the parent company. the second stage of the multi-stage DEA model showed that the CCR model was slightly more efficient than the parent company and the BCC model was more efficient than the parent.the overall efficiency value of the multistage DEA model, calculated by multipointing the efficiency value of the first stage by the second stage, was more efficient than the parent. Conclusion: The results of this study show that the efficiency of supply chian quality management performance and profitability in the defense industry can be analyzed for the first time using the multistage DEA/Entropy model to identify specific inefficiencies and support objective decision making.

• 디자인학연구
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• 제9권
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• pp.801-810
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• 1994

Design Problems are often both multidimensional and highly interactive. Very rarely does any part of a designed thing serve only one purpose. The activity of designing is thus a goal-directed activity and normally a goal-directed problem-solving activity. This means, problem solving is finding a way to get from some initial situation to a desired goal. Designers are transforming agents within a society whose goals are to improve the human condition through physical metamorphosis. Many theorist have agreed that designing involves problem solving or decision making. Accordingly evaluation plays an essential role in design activity. The evaluation factors include all attributes that have levels specified by quantitative and qualitative objectives Alternatives in multi-objective decision prOblems generally possess numerous attributes by which they can be described and compared. The evaluation factors include all attributes that have levels specified by quantitative and qualitative objectives. However since qualitative factors are difficult to quantify as numeral estimates, these factors have tended to be ignored without regard for their importance to human content. We adapted the Accumulative Evaluation Model as an evaluation algorithm for IDES. Industrial Design Evaluation System (IDES) consists of 3 major modules ( 1 Design Element, 2.Matrix, 3.Evaluation). It is intended to be an aid for design evaluation. The luther thinks IDES is a new design evaluation approach which could provide effective rating of design values to make value judgements. It is an attempt to provide industrial designers with access to design evaluation. The author's aim is to produce an Object-Oriented Evaluation System which can guide the designers and decision makers under complex design projects. It uses\ulcorner an Object-Oriented Programming for this prototype, Because of managing complexity (Flexibility and Reusability) and improving productivity(Extensibility & Maintainability and Programming by User) in software development process. The author has chose the C++ because it is a hybrid, rather than pure Object-Oriented Language.

• 한국도로학회논문집
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• 제18권3호
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• pp.47-57
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• 2016

PURPOSES : This study aims to examine the differences between the existing traffic demand forecasting method and the traffic demand forecasting method considering future regional development plans and new road construction and expansion plans using a four-step traffic demand forecast for a more objective and sophisticated national highway maintenance. This study ultimately aims to present future pavement deterioration and budget forecasting planning based on the examination. METHODS : This study used the latest data offered by the Korea Transport Data Base (KTDB) as the basic data for demand forecast. The analysis scope was set using the Daejeon Metropolitan City's O/D and network data. This study used a traffic demand program called TransCad, and performed a traffic assignment by vehicle type through the application of a user equilibrium-based multi-class assignment technique. This study forecasted future traffic demand by verifying whether or not a realistic traffic pattern was expressed similarly by undertaking a calibration process. This study performed a life cycle cost analysis based on traffic using the forecasted future demand or existing past pattern, or by assuming the constant traffic demand. The maintenance criteria were decided according to equivalent single axle loads (ESAL). The maintenance period in the concerned section was calculated in this study. This study also computed the maintenance costs using a construction method by applying the maintenance criteria considering the ESAL. The road user costs were calculated by using the user cost calculation logic applied to the Korean Pavement Management System, which is the existing study outcome. RESULTS : This study ascertained that the increase and decrease of traffic occurred in the concerned section according to the future development plans. Furthermore, there were differences from demand forecasting that did not consider the development plans. Realistic and accurate demand forecasting supported an optimized decision making that efficiently assigns maintenance costs, and can be used as very important basic information for maintenance decision making. CONCLUSIONS : Therefore, decision making for a more efficient and sophisticated road management than the method assuming future traffic can be expected to be the same as the existing pattern or steady traffic demand. The reflection of a reliable forecasting of the future traffic demand to life cycle cost analysis (LCCA) can be a very vital factor because many studies are generally performed without considering the future traffic demand or with an analysis through setting a scenario upon LCCA within a pavement management system.