• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.642-652
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• 2007

Many contracting firms and project managers in the construction industry have started to utilize multi objective optimization methods to handle multiple conflicting goals for completing the project within the stipulated time and budget with required quality and safety. These optimization methods have increased the pressure on decision makers to search for an optimal resources utilization plan that optimizes simultaneously the total project cost, completion time, and crashing cost by considering indirect cost, contractual penalty cost etc., practically charging them in terms of direct cost of the project which is fuzzy in nature. This paper presents a multiple fuzzy goal programming model (MFGP) that supports decision makers in performing the challenging task. The model incorporates the fuzziness which stems from the imprecise aspiration levels attained by the decision maker to these objectives that are quantified through fuzzy linear membership function. The membership values of these objectives are then maximized which forms the fuzzy decision. The problem is solved using LINGO 8 optimization solver and the best compromise solution is identified. Comparison between solutions of MFGP, fuzzy multi objective linear programming (FMOLP) and multiple goal programming (MGP) are also presented. Additionally, an interactive decision making process is developed to enable the decision maker to interact with the system in modifying the fuzzy data and model parameters until a satisfactory solution is obtained. A case study is considered to demonstrate the feasibility of the proposed model for optimization of project network parameters in the construction industry.

• 대한산업공학회지
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• 제38권1호
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• pp.57-66
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• 2012

The paper deals with the development of a model for group decision making under multiple criteria. The Multi-criteria group decision making (MCGDM) is the process to determine the best compromise solution in a set of competing alternatives that are evaluated by decision makers having their own preferences on conflicting objectives. For MCGDM, we propose a Mixed-Integer Programming (MIP) model that implements a revised median approach by noticing that the original median approach cannot consider the willingness to reject and the indifferent preference conditions. The proposed MIP model tries to select a common best Pareto-optimal solution by maximizing the overall desirability considering the willingness to reject and the indifferent preference that represent the tolerance measure of each decision maker. To evaluate the effectiveness of the proposed model, we compared the results of the proposed model with those of the median approach. The results showed that the proposed MIP model produces more realistic and better compromised alternative by incorporating the decision maker's willingness to reject and the indifferent preferences over each criteria.

• Journal of Mechanical Science and Technology
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• 제20권3호
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• pp.366-375
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• 2006

In this paper, it is intended to introduce a method to solve multi-objective optimization problems and to evaluate its performance. In order to verify the performance of this method it is applied for a vertical roller mill for Portland cement. A design process is defined with the compromise decision support problem concept and a design process consists of two steps: the design of experiments and mathematical programming. In this process, a designer decides an object that the objective function is going to pursuit and a non-linear optimization is performed composing objective constraints with practical constraints. In this method, response surfaces are used to model objectives (stress, deflection and weight) and the optimization is performed for each of the objectives while handling the remaining ones as constraints. The response surfaces are constructed using orthogonal polynomials, and orthogonal array as design of experiment, with analysis of variance for variable selection. In addition, it establishes the relative influence of the design variables in the objectives variability. The constrained optimization problems are solved using sequential quadratic programming. From the results, it is found that the method in this paper is a very effective and powerful for the multi-objective optimization of various practical design problems. It provides, moreover, a reference of design to judge the amount of excess or shortage from the final object.

• 한국수자원학회논문집
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• 제51권4호
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• pp.301-311
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• 2018

지구 온난화가 심화됨에 따라 도시지역에서 집중호우에 의한 침수 피해가 증가하는 추세이다. 이러한 지구온난화에 의한 기후변화의 변동성은 IPCC 5차 보고서(2014)에서도 기술되어 있으며 기후변화에 의한 강수 패턴의 변화, 수문시스템의 변화 등 수자원 불확실성의 증가에 대하여 시사하고 있다. 최근 서울이나 부산과 같은 대도시의 관로의 수용 범위를 초과하는 국지성 호우가 발생하여 큰 피해를 초래하였다. 도시지역의 침수는 1차적으로 우수관거 통수능 부족에 의한 내수범람이 발생하고 방류구와 인접한 하천의 외수범람이 발생한다. 인구가 밀집되어 있는 도시지역에서 발생하는 침수는 인명피해 뿐만 아니라 도로, 교량, 지하공간 침수 및 파괴를 복구하기 위한 사회 경제적 피해를 동반하기 때문에 농촌, 산지 지역에 비해 피해량이 크다. 또한 도시개발에 인한 불투수면적 증가, 강우 유출시 출구부까지의 짧은 도달시간, 배수시설의 통수능부족 등 다양한 원인이 침수피해를 증대시킨다. 본 연구에서는 집중호우에 취약한 지역을 선정하고 XP-SWMM을 이용하여 내수침수 모의를 실시하였다. 또한 시범지역에 관로 개량, 우수저류지 설치, 우수펌프장 설치와 같은 홍수방어대안을 적용하여 각각의 침수모의를 실시하였으며 해당유역을 격자별로 분할하여 대안별 침수데이터를 추출하였다. 또한 격자별로 가장 적합한 구조적 홍수방어대안을 제시하기 위해 침수시간, 최대침수심, 구조물 설치비용을 평가요소로 이용하였으며 MCDM 기법 중 하나인 Compromise Programming 기법을 적용하였다. 본 연구에서는 동일 유역이라도 지리적 여건에 따라 대안의 선호도가 다르다는 점을 반영하고자 하였으며, Spatial Multi-Criteria Decision Making을 적용하여 지역특성을 고려한 홍수방어대안을 선정하는 방법에 대하여 연구하였다.

• 한국경영과학회지
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• 제41권2호
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• pp.53-65
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• 2016

Static wireless multi-hop networks, such as wireless mesh networks and wireless sensor networks have proliferated in recent years because of they are easy to deploy and have low installation cost. Two key measures are used to evaluate the performance of a multicast tree algorithm or protocol : end-to-end delay and the number of transmissions. End-to-end delay is the most important measure in terms of QoS because it affects the total throughput in wireless networks. Delay is similar to the hop count or path length from the source to each destination and is directly related to packet success ratio. In wireless networks, each node uses the air medium to transmit data, and thus, bandwidth consumption is related to the number of transmission nodes. A network has many transmitting nodes, which will cause many collisions and queues because of congestion. In this paper, we optimize two metrics through a guaranteed delay scheme. We provide an integer linear programming formulation to minimize the number of transmissions with a guaranteed hop count and preprocessing to solve the aforementioned problem. We extend this scheme not only with the guaranteed minimum hop count, but also with one or more guaranteed delay bounds to compromise two key metrics. We also provide an explanation of the proposed heuristic algorithm and show its performance and results.

• 한국수자원학회논문집
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• 제40권12호
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• pp.969-983
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• 2007

본 연구에서는 도시화로 인해 왜곡된 물순환을 치수, 이수, 수질관리 등의 측면에서 건전화시키기 위해 지속가능한 유역통합관리 계획을 수립하기 위한 10단계의 절차와 적용방법을 개발하여 제시하였으며 이 중 Step 2에 해당하는 문제점 도출 및 우선순위 결정 단계를 수행하였다. 유역의 잠재적인 위험도를 나타내는 홍수피해잠재능(PFD), 건천잠재능(PSD), 수질오염잠재능(PWQD), 유역평가지수(WEI)를 산정하기 위해 다기준 의사결정기법과 지속가능성평가지수 개념을 사용하였다. 사용된 다기준 의사결정 기법들은 복합계획법, 타협계획법, Regime, ELECTRE II, EVAMIX 방법이며 자료의 가용성과 목적(예비타당성, 타당성)에 따라 다르게 사용될 수 있다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.437-437
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• 2018

본 연구는 댐 후보지에 대한 우선순위 분석이 결측 정보에 따라 다기준 의사결정 방법 및 결측정보 접근방법에 따라 어떻게 달라지는지를 조사하였다. 전략환경평가(Strategic Environmental Assessment, SEA)는 한국의 댐 건설 장기 계획에서 환경 및 생태학적 영향을 기반으로 한 지속가능한 댐 후보지 선정에 적용되고 있다. 그러나 특정 정보가 결측된 경우 SEA는 댐 후보지를 선정하는 데 어려움이 있다. 본 연구에서는 다기준 의사결정 방법으로 AHP, ELECTRE III, PROMETHEE II, Compromise Programming을 적용하였고, 결측 정보 보완을 위해 이항분포와 균등분포형을 사용하였다. 본 연구에서는 전국의 댐 선정 후보지에 적용하여 다중 기준 의사 결정기법과 정보 생성 방법에 의존하여 결과를 비교하였다. 그 결과, 이항분포형을 적용한 결과가 균등분포형을 적용한 결과보다 보다 명백한 우선순위를 보여 주었다. 또한, 다기준 의사결정방법에 따라서는 댐선정 후보지 결과가 달라지지 않는 것으로 나타났다. 따라서, 다기준 의사결정방법 적용시, 결측 정보를 생성하기 위해 이항분포를 사용하면 균등분포 적용시보다 우선순위를 제공하는데 더 효과적이라고 판단된다.

• International Journal of Naval Architecture and Ocean Engineering
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• 제11권1호
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• pp.44-51
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• 2019

Designing sophisticate ship structures that satisfy several design criteria simultaneously with minimum weight and cost is an important engineering issue. For a ship structure composed of a shell and stiffeners, this issue is more serious because their mutual effect has to be addressed. In this study, a two-stage optimization method is proposed for the conceptual design of stiffeners in a ship's prow. In the first stage, a topology optimization method is used to determine a potential stiffener distribution based on the optimal results, whereupon stiffeners are constructed according to stiffener generative theory and the material distribution. In the second stage, size optimization is conducted to optimize the plate and stiffener sections simultaneously based on a parametric model. A final analysis model of the ship-prow structure is presented to assess the validity of this method. The analysis results show that the two-stage optimization method is effective for stiffener conceptual design, which provides a reference for designing actual stiffeners for ship hulls.

• Environmental Engineering Research
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• 제15권2호
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• pp.63-70
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• 2010

In this study, the response surface method and experimental design were applied as an alternative to conventional methods for the optimization of coagulation tests. A central composite design, with 4 axial points, 4 factorial points and 5 replicates at the center point were used to build a model for predicting and optimizing the coagulation process. Mathematical model equations were derived by computer simulation programming with a least squares method using the Minitab 15 software. In these equations, the removal efficiencies of turbidity and total organic carbon (TOC) were expressed as second-order functions of two factors, such as alum dose and coagulation pH. Statistical checks (ANOVA table, $R^2$ and $R^2_{adj}$ value, model lack of fit test, and p value) indicated that the model was adequate for representing the experimental data. The p values showed that the quadratic effects of alum dose and coagulation pH were highly significant. In other words, these two factors had an important impact on the turbidity and TOC of treated water. To gain a better understanding of the two variables for optimal coagulation performance, the model was presented as both 3-D response surface and 2-D contour graphs. As a compromise for the simultaneously removal of maximum amounts of 92.5% turbidity and 39.5% TOC, the optimum conditions were found with 44 mg/L alum at pH 7.6. The predicted response from the model showed close agreement with the experimental data ($R^2$ values of 90.63% and 91.43% for turbidity removal and TOC removal, respectively), which demonstrates the effectiveness of this approach in achieving good predictions, while minimizing the number of experiments required.