• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.9
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• pp.557-567
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• 2016

In this study, the optimal design of heat exchangers, including the evaporator and condenser of a solar-heating ocean thermal energy conversion (SH-OTEC), is investigated. The power output of the SH-OTEC is assumed to be 100 kW, and the SH-OTEC uses the working fluid of R134a and high-performance commercial tubes. The surface heat transfer area and the pressure drop were strongly dependent on the number of tubes, as well as the number of tube passes. To solve the reciprocal tendency between the heat transfer area and pressure drop with respect to the number of tubes, as well as the number of tube passes, a genetic algorithm (GA) with two objective functions of the heat transfer area (the capital cost) and operating cost (pressure drop) was used. Optimal results delineated the feasible regions of heat transfer area and operating cost with respect to the pertinent number of tubes and tube passes. Pareto fronts of the evaporator and condenser obtained from multi-objective GA provides designers or investors with a wide range of optimal solutions so that they can select projects suitable for their financial resources. In addition, the surface heat transfer area of the condenser took up a much higher percentage of the total heat transfer area of the SH-OTEC than that of the evaporator.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.1
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• pp.69-78
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• 2011

In this study, an optimization method using multi-objective genetic algorithm(MOGA) has been proposed to develop a fuzzy control algorithm that can effectively control a smart tuned mass damper(TMD). A 76-story benchmark building subjected to wind load was selected as an example structure. The smart TMD consists of 100kN MR damper and the natural period of the smart TMD was tuned to the first mode natural period of the example structure. Damping force of MR damper is controlled to reduce the wind-induced responses of the example structure by a fuzzy logic controller. Two input variables of the fuzzy logic controller are the acceleration of 75th floor and the displacement of the smart TMD and the output variable is the command voltage sent to MR damper. Multi-objective genetic algorithm(NSGA-II) was used for optimization of the fuzzy logic controller and the acceleration of 75th story and the displacement of the smart TMD were used as objective function. After optimization, a series of fuzzy logic controllers which could appropriately reduce both wind responses of the building and smart TMD were obtained. Based on numerical results, it has been shown that the control performance of the smart TMD is much better than that of the passive TMD and it is even better than that of the sample active TMD in some cases.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.17-34
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• 2022

This paper develops a model for dynamic station assignment to optimize the Demand Responsive Transit (DRT) operation. In the process of optimization, we use the bus travel time as a variable for DRT management. In addition, walking time, waiting time, and delay due to detour to take other passengers (detour time) are added as optimization variables and entered for each DRT passenger. Based on a network around Anaheim, California, reserved origins and destinations of passengers are assigned to each demand responsive bus, using K-means clustering. We create a model for selecting the dynamic station and bus route and use Non-dominated Sorting Genetic Algorithm-III to analyze seven scenarios composed combination of the variables. The result of the study concluded that if the DRT operation is optimized for the DRT management, then the bus travel time and waiting time should be considered in the optimization. Moreover, it was concluded that the bus travel time, walking time, and detour time are required for the passenger.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.803-812
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• 2018

The purpose of this study is to develop Particle Swarm Optimization (PSO) automatic calibration algorithm with multi-objective functions by Python, and to evaluate the applicability by applying the algorithm to the Soil and Water Assessment Tool (SWAT) watershed modeling. The study area is the upstream watershed of Gongdo observation station of Anseongcheon watershed ($364.8km^2$) and the daily observed streamflow data from 2000 to 2015 were used. The PSO automatic algorithm calibrated SWAT streamflow by coefficient of determination ($R^2$), root mean square error (RMSE), Nash-Sutcliffe efficiency ($NSE_Q$), and especially including $NSE_{INQ}$ (Inverse Q) for lateral, base flow calibration. The results between automatic and manual calibration showed $R^2$ of 0.64 and 0.55, RMSE of 0.59 and 0.58, $NSE_Q$ of 0.78 and 0.75, and $NSE_{INQ}$ of 0.45 and 0.09, respectively. The PSO automatic calibration algorithm showed an improvement especially the streamflow recession phase and remedied the limitation of manual calibration by including new parameter (RCHRG_DP) and considering parameters range.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.75-89
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• 1999

위험물차량사고는 일반차량의 교통사고시 발생하는 인명피해, 재산피해, 교통지체 외에 부가적으로 환경적 영향에 의한 엄청난 인명 및 재산손실을 유발시킬 수 있다. 따라서 이러한 위험물차량사고를 예방하고 피해를 최소로 줄이기 위해서는 위험물수송경로의 신중하고 체계적인 결정이 필수적이라 할 수 있다. 따라서, 본 연구는 위험물차량의 수송경로를 결정할 때 고려해야 할 여러 가지의 기준 및 목표에 따라 위험물수송경로를 설정하는 모형을 제시함으로써 위험물수송에 수반되는 위험을 최소화하면서 위험물차량의 통행시간, 거리, 비용 등을 최적화하여 위험물수송의 안전 및 운영효율성을 향상시키고자 한다. 먼저, 위험물 수송경로의 기준지표로 사용될 위험도를 나타내기 위해 사고율과 피해가능규모를 구하도록 사 고건수, 링크 주변노출인구, 링크상의 노출인구, 밀도 등을 변수로 하는 모형식을 제안하고, 두 번째로 위험물 수송을 위한 최적경로를 산출하기 위해 위험도와 통행시간을 목적함수로 하는 다목적계획모형을 제안하였고 기존의 최적경로 알고리즘을 적용하여 최적경로를 산출하였다. 마지막으로 실제 수도권지역을 대상으로 본 연구에서 제안한 모형을 적용하고 현재 일반적으로 사용되는 최단경로와 비교.분석하였다. 모형적용결과, 링크주변인구만을 고려하는 기존 모형에 비해 링크상의 인구를 함께 고려함으로써 좀더 실제적으로 교통상황을 충분히 반영한 피해규모를 산정하였다. 또한, 본 연구에서 제안한 위험도와 통행시간에 0.5의 비중을 주는 다목적모형이 기존의 위험도모형에 비해 충분한 안전성을 확보하면서 최소 4%, 최대 12%의 통행시간 개선의 효과가 있음을 나타냈다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.1
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• pp.144-151
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• 2003

In this paper, an optimum design problem for endosseous implant in dentistry is studied to find best implant design. An optimum design problem is formulated to reduce stresses arising at the cortical as well as cancellous bones, in which sufficient design parameters are chosen fur design definition that encompasses major implants in popular use. Optimization at once (OAO) with the large number of design variables, however, causes too costly solution or even failure to converge. A concept of multilevel optimization (MLO) is employed to this end, which is to group the design variables of similar nature, solve the sub-problem of smaller size fur each group in sequence, and this is iterated until convergence. Each sub-problem is solved based on the response surface method (RSM) due to its efficiency for small sized problem. Favorable solution is obtained by the MLO, which is compared to both solutions made by RSM and sequential quadratic programming (SQP) in the OAO problem.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.292-296
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• 2010

본 연구에서는 상대적으로 소규모 홍수저감시설인 천변저류지의 설치를 통하여 대규모 유역 하도 전체에서의 홍수위 저감효과를 평가하고 그 효율을 극대화 하는 방안을 제시하였다. 본 연구에 적용한 다목적 최적화 기법(Multi-objective Optimization)으로는 NSGA-II(Non-dominated Sorting Genetic Algorithm II) 알고리즘을 적용하였으며 천변저류지 설치에 따른 수위 영향구간 분석 및 유역 전체 하도구간에서 전반적으로 발생하는 수리, 수문학적인 변화 평가 및 천변저류지 최적 조합을 선정하기 위하여 천변저류지의 용량을 최소화하면서 하도 전 구간에서의 수위 저감량을 최대화할 수 있도록 최적화 알고리즘의 목적함수를 설정하였다. 천변저류지 설치에 따른 홍수량의 변화를 해석하기 위하여 안성천 유역에 대하여 동역학적 홍수추적을 수행하였으며 저류형 구조물의 설치에 따른 홍수량 저감효과 및 그에 따른 홍수위의 변화를 동시에 해석하기 위하여 UNET 모형을 기반으로 한 HEC-RAS 부정류 해석을 실시하였다. 천변저류지 조합별로 다양한 경우의 수가 존재하므로 HEC-RAS 구동 모듈인 HECRAS Controller를 Visual Basic으로 코딩된 최적화 알고리즘 프로그램과 연동함으로써 각 경우의 수별로 동역학적 홍수추적 및 부정류 해석을 실시함으로써 천변저류지 조합별 각 측점에서의 홍수량 및 홍수위를 산정하여 저류지 용량을 최소화하면서 각 하도 측점별 수위저감량을 최대화 하는 최적해 집단(Pareto Front)을 산정하여 제시하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.115-127
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• 2020

In this paper, a sustainable close-loop supply chain (SCLSC) model is proposed for effectively managing the production, distribution and handling process of mobile phone. The proposed SCLSC model aims at maximizing total profit as economic factor, minimizing total CO₂ emission amount as environmental factor, and maximizing social influence as social factor in order to reinforce sustainability in it. Since these three factors are represented as each objective function in modeling, the proposed SCLSC model can be taken into consideration as a multi-objective optimization problem and solved using a hybrid genetic algorithm (HGA) approach. In numerical experiment, three different scales of the SCLSC model are presented and the efficiency of the HGA approach is proved using various measures of performance.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.49-62
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• 2024

In this paper, a sustainable closed-loop supply chain (SCLSC) network model is proposed for domestic mobile phone industry. Economic, environmental and social factors are respectively considered for reinforcing the sustainability of the SCLSC network model. These three factors aim at minimizing total cost, minimizing total amount of CO₂ emission, and maximizing total social influence resulting from the establishment and operation of facilities at each stage of the SCLSC network model. Since they are used as each objective function in modeling, the SCLSC network model can be a multi-objective optimization problem. A mathematical formulation is used for representing the SCLSC network model and a hybrid meta-heuristic approach is proposed for efficiently solving it. In numerical experiment, the performance of the proposed hybrid meta-heuristic approach is compared with those of conventional meta-heuristic approaches using some scales of the SCLSC network model. Experimental results shows that the proposed hybrid meta-heuristic approach outperforms conventional meta-heuristic approaches.

• Korean Chemical Engineering Research
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• v.55 no.3
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• pp.332-340
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• 2017

This study aims to propose a new optimization-based approach for design and analysis of the stand-alone hybrid energy supply system using renewable energy sources (RES). In the energy supply system, we include multiple energy production technologies such as Photovoltaics (PV), Wind turbine, and fossil-fuel-based AC generator along with different types of energy storage and conversion technologies such as battery and inverter. We then select six different regions of Korea to represent various characteristics of different RES potentials and demand profiles. We finally designed and analyzed the optimal RES stand-alone energy supply system in the selected regions using multiobjective optimization (MOOP) technique, which includes two objective functions: the minimum cost and the minimum $CO_2$ emission. In addition, we discussed the feasibility and expecting benefits of the systems by comparing to conventional systems of Korea. As a result, the region of the highest RES potential showed the possibility to remarkably reduce $CO_2$ emissions compared to the conventional system. Besides, the levelized cost of electricity (LCOE) of the RES-based energy system is identified to be slightly higher than conventional energy system: 0.35 and 0.46 $/kWh, respectively. However, the total life-cycle emission of $CO_2$ ($LCE_{CO2}$) can be reduced up to 470 g$CO_2$/kWh from 490 g$CO_2$/kWh of the conventional systems.