• 산업경영시스템학회지
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• 제40권4호
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• pp.112-119
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• 2017

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

• Journal of the Korean Data and Information Science Society
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• 제26권6호
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• pp.1479-1494
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• 2015

최적의 포트폴리오를 선택하기 위한 연구는 평균-분산모형을 시작으로 다양하게 진행되어 왔다. 과거에는 위험자산의 확률분포가 정규분포를 따른다고 가정하여, 투자자가 보유한 위험자산의 분산이 최소화되고 기대수익률이 최대가 되도록 포트폴리오를 구성하도록 하였다. 그러나 실제 위험자산의 분포에는 극단적인 사건들이 많이 발생하기 때문에 정규분포보다 훨씬 꼬리부분이 두꺼우며, 또한 왼쪽꼬리와 오른쪽꼬리가 대칭적이지도 않은 것으로 밝혀졌다. 이에 본 논문에서는 위험자산의 확률분포를 극단치 이론에서 널리 사용되는 일반화 파레토분포 (GPD)로 모형화하였고 체계적인 위험의 추정을 위하여 VaR를 이용하는 한편, 최적의 포트폴리오의 탐색을 위해서는 유전자 알고리즘을 사용하였다. 제안 방법의 적정성을 확인하기 위해 국내 증시에서 최적 포트폴리오를 탐색해 보았으며, 그 결과 GPD로 투자자산의 위험을 추정하였을 때 가장 좋은 결과를 얻을 수 있었다.

• International Journal of Fluid Machinery and Systems
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• 제9권2호
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• pp.143-149
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• 2016

In this study, a method for the multi-objective optimization of an impeller for a centrifugal compressor using fluid-structure interaction (FSI) and response surface method (RSM) was proposed. Numerical simulation was conducted using ANSYS CFX and Mechanical with various configurations of impeller geometry. Each design parameter was divided into 3 levels. A total of 15 design points were planned using Box-Behnken design, which is one of the design of experiment (DOE) techniques. Response surfaces based on the results of the DOE were used to find the optimal shape of the impeller. Two objective functions, isentropic efficiency and equivalent stress were selected. Each objective function is an important factor of aerodynamic performance and structural safety. The entire process of optimization was conducted using the ANSYS Design Xplorer (DX). The trade-off between the two objectives was analyzed in the light of Pareto-optimal solutions. Through the optimization, the structural safety and aerodynamic performance of the centrifugal compressor were increased.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권5호
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• pp.325-331
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• 2004

The multiobjective optimization (MO) problem usually includes the conflicting objectives and the use of conventional optimization algorithms for MO problem does not so good approach to obtain an effective optimal solution. In this paper, genetic algorithm (GA) as an effective method is used to solve such MO problem of brushless DC motor (BLDCM). 3D equivalent magnetic circuit network (EMCN) method which enables us to reduce the computational burden is also used to consider the 3D structure of BLDCM. In order to effectively obtain a set of Pareto optimal solutions in MO problem, ranking method proposed by Fonseca is applied. The objective functions are decrease of cogging torque and increase of torque respectively. The airgap length, teeth width and magnetization angle of PM are selected for the design variables. The experimental results are also shown to confirm the validity of the optimization results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.162-164
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• 2007

This paper presents a "window-zoom-out" optimization strategy with relatively fewer sampling data. In this method, an optimal Latin hypercube sampling experiment based on multi-objective Pareto optimization is developed to obtain the sampling data. The response surface method with multiquadric radial basis function combined with (1+$\lambda$) evolution strategy is used to find the global optimal point. The proposed method is verified with numerical experiments.

• Industrial Engineering and Management Systems
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• 제16권1호
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• pp.52-63
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• 2017

The inventory level of concurrent spare parts (CSP) has a significant impact on the availability of a weapon system. A failure rate function might be of particular importance in deciding the CSP inventory level. We developed a CSP optimization model which provides a compromise between purchase costs and shortage costs on the basis of the Weibull and the exponential failure rate functions, assuming that a failure occurs according to the (non-) homogeneous Poisson process. Computational experiments using the data obtained from the Korean Navy identified that, throughout the initial provisioning period, the optimization model using the exponential failure rate tended to overestimate the optimal CSP level, leading to higher purchase costs than the one using the Weibull failure rate. A Pareto optimality was conducted to find an optimal combination of these two failure rate functions as input parameters to the model, and this provides a practical solution for logistics managers.

• 한국정밀공학회지
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• 제25권2호
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• pp.88-95
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• 2008

With society focusing more and more on environmental issues, the recycling of materials of all types has become an important concern. In this paper, optimization method is developed for reducing cost and improving quality in mill scale recycling. An experimental investigation into the process parameter effects is presented to determine the optimum configuration of parameters for performance, quality and cost. Taguchi's optimization approach was used to obtain the optimal parameters. The significant parameters were identified and their effects on mill scale recycling were studied. As a results, a confirmation experiment with the optimal levels of process parameters was carried out in order to demonstrate the effectiveness of the Taguchi method.

• Steel and Composite Structures
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• 제14권4호
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• pp.397-408
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• 2013

This paper deals with multiobjective optimization of symmetrically laminated composite truncated circular conical shells subjected to external uniform pressure load and thermal load. The design objective is the maximization of the weighted sum of the critical buckling load and fundamental frequency. The design variable is the fibre orientations in the layers. The performance index is formulated as the weighted sum of individual objectives in order to obtain optimal solutions of the design problem. The first-order shear deformation theory (FSDT) is used in the mathematical formulation of laminated truncated conical shells. Finally, the effect of different weighting factors, length-to-radius ratio, semi-cone angle and boundary conditions on the optimal design is investigated and the results are compared.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.1441-1446
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• 2003

The design optimization of the plate heat exchanger with staggered pin arrays for a fixed volume is performed numerically. The flow and thermal fields are assumed to be a streamwise-periodic flow and heat transfer with constant wall temperature and they are solved by using the finite volume method. The optimization is carried out by using the sequential linear programming (SLP) method and the weighting method is used for solving the multi-objective problem. The results show that the optimal design variables for the weighting coefficient of 0.5 are as follows; S=6.497mm, P=5.496mm, $D_1=0.689mm$, and $D_2=2.396mm$. The Pareto optimal solutions are also presented.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.43-48
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• 2003

In this study the optimization of plate-fin type heat sink for the thermal stability is performed numerically. The optimum design variables are obtained when the temperature rise and the pressure drop are minimized simultaneously. The flow and thermal fields are predicted using the finite volume method and the optimization is carried out by using the sequential quadratic programming (SQP) method which is widely used in the constrained nonlinear optimization problem. The results show that when the temperature rise is less than 34.6 K, the optimal design variables are as follows; $B_{1}$ = 2.468 mm, $B_{2}$ = 1.365 mm, and t = 10.962 mm. The Pareto optimal solutions are also presented for the pressure drop and the temperature rise.