• 한국지능시스템학회논문지
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• 제17권1호
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• pp.66-71
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• 2007

급속도로 변화하는 환경에 적응하고 환경의 변화에 대한 신속한 응답능력을 향상시키고, 에이전트간 의사결정의 지속시간을 줄이기 위하여, 사용자의 선호도와 선택(alternative)의 유도가 요구된다. 본 논문에서는 사회적(Pareto) 최적성이라는 관점에서 에이전트들이 제안한 해를 가지고 퍼지 의사결정에 기반한 멀티에이전트의 효율적인 조정방안을 제안한다. 이 방법은 가중치를 사용하여 최적의 선택을 생성하고 승자 에이전트의 속성 중요도를 계산한 다음 속성들의 우선순위를 나타냈다. 그리고 기존의 방법과 가중치를 사용한 방법을 분석해보았다.

• Journal of Magnetics
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• 제21권4호
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• pp.660-665
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• 2016

The electromagnetic apparatus plays an important role in high power electrical systems. It is of great importance to provide an effective approach for the optimization of the high power electromagnetic apparatus. However, premature convergence and few Pareto solution set of the optimization for electromagnetic apparatus always happen. This paper proposed a modified multi-objective particle swarm optimization algorithm based on the niche sorting strategy. Applying to the modified algorithm, this paper guarantee the better Pareto optimal front with an enhanced distribution. Aiming at shortcomings in the closing bounce and slow breaking velocity of electromagnetic apparatus, the multi-objective optimization model was established on the basis of the traditional optimization. Besides, by means of the improved multi-objective particle swarm optimization algorithm, this paper processed the model and obtained a series of optimized parameters (decision variables). Compared with other different classical algorithms, the modified algorithm has a satisfactory performance in the multi-objective optimization problems in the electromagnetic apparatus.

• 한국수자원학회논문집
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• 제40권9호
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• pp.687-696
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• 2007

본 연구는 다목적 유전자알고리즘을 이용하여 Tank 모형의 매개변수를 추정하는데 있어서 선호적순서화(preference ordering)를 적용한 연구로써, 목적함수의 개수가 여러 개인 경우에 발생할 수 있는 파레토최적화의 단점을 해결하기 위한 것이다. 최적화를 위한 목적함수는 모두 4가지를 사용하였으며, 선호적순서화를 통해서 구한 2차 효율성(2nd order efficiency)을 가지면서 정도(degree)가 3인 4개의 해 중에서 1개의 해만을 최우선해로 선정하였다. NSGA-II로 도출된 최우선해의 적합성을 살펴보기 위해서, 자동보정방법인 Powell 방법과 SGA(simple genetic algorithm)를 매개변수 자동보정 방법으로 이용하고 하나의 단일목적함수로 사용해서 최적화한 결과와 비교해보았으며, 비교결과 다목적 유전자 알고리즘을 4개의 목적함수에 모두 적용해서 한번에 도출된 매개변수를 이용한 결과가 보정기간뿐만 아니라 검정기간에 대해서도 비교적 양호한 결과를 나타내는 것으로 나타났다.

• 한국수자원학회논문집
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• 제43권12호
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• pp.1011-1027
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• 2010

모형의 구조, 모델링에 사용되는 자료, 매개변수 등에 포함된 다양한 불확실성 원인들은 수문모의 및 예측결과에 있어 불확실성을 야기한다. 본 연구에서는 강우-유출 및 강우-유사유출 모의가 가능한 분포형 강우-유사-유출 모형을 용담댐 상류유역인 천천유역에 적용하여 수문곡선 및 유사량곡선의 재현성을 평가하고, 다중최적화기법인 MOSCEM을 이용하여 강우-유출 모듈, 강우-유사유출 모듈의 매개변수를 독립적으로 보정한 경우(Case I과 II), 그리고 두 모듈이 결합된 강우-유사-유출 모형의 매개변수를 동시에 보정한 경우(Case III)에 대하여 Pareto 최적해를 추정하고, 이에 따른 수문 예측결과의 불확실성을 평가한다. 매개변수 불확실성의 전이에 따른 수문곡선의 불확실성 평가 결과(Case I), 모의기간 동안 고유량보다는 저유량 부분에서 불확실성 범위가 두드러졌으며, 이에 반해, 유사량곡선의 경우(Case II) 저농도보다는 고농도 부분에서 불확실성 범위가 넓게 분포하였다. 강우-유사-유출 모형의 매개변수의 불확실성을 동시에 추정한 경우 수문곡선 및 유사량곡선 모두 Case I과 II에 비해 모의기간 전반에 걸쳐 불확실성 범위가 넓게 분포되었으며, 매개 변수의 불확실성으로 인해 대상유역내 격자별 침식 및 퇴적 공간분포 양상이 상이하게 나타났다.

• Journal of Mechanical Science and Technology
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• 제19권5호
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• pp.1080-1086
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• 2005

The preliminary design optimization of multi-stage spur gear reduction units has been a subject of considerable interest, since many high-performance power transmission applications (e.g., automotive and aerospace) require high-performance gear reduction units. There are multiple objectives in the optimal design of multi-stage spur gear reduction unit, such as minimizing the volume and maximizing the surface fatigue life. It is reasonable to formulate the design of spur gear reduction unit as a multi-objective optimization problem, and find an appropriate approach to solve it. In this paper an interactive physical programming approach is developed to place physical programming into an interactive framework in a natural way. Class functions, which are used to represent the designer's preferences on design objectives, are fixed during the interactive physical programming procedure. After a Pareto solution is generated, a preference offset is added into the class function of each objective based on whether the designer would like to improve this objective or sacrifice the objective so as to improve other objectives. The preference offsets are adjusted during the interactive physical programming procedure, and an optimal solution that satisfies the designer's preferences is supposed to be obtained by the end of the procedure. An optimization problem of three-stage spur gear reduction unit is given to illustrate the effectiveness of the proposed approach.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.2125-2138
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• 2023

The printed circuit heat exchanger (PCHE) with airfoil fins has the benefits of high compactness, high efficiency and superior heat transfer performance. A novel multi-objective optimization approach is presented to design the airfoil fin PCHE in this paper. Three optimization design variables (the vertical number, the horizontal number and the staggered number) are obtained by means of dimensionless airfoil fin arrangement parameters. And the optimization objective is to maximize the Nusselt number (Nu) and minimize the Fanning friction factor (f). Firstly, in order to investigate the impact of design variables on the thermal-hydraulic performance, a parametric study via the design of experiments is proposed. Subsequently, the relationships between three optimization design variables and two objective functions (Nu and f) are characterized by an improved particle swarm optimization-backpropagation artificial neural network. Finally, a multi-objective optimization is used to construct the Pareto optimal front, in which the non-dominated sorting genetic algorithm II is used. The comprehensive performance is found to be the best when the airfoil fins are completely staggered arrangement. And the best compromise solution based on the TOPSIS method is identified as the optimal solution, which can achieve the requirement of high heat transfer performance and low flow resistance.

• International Journal of Automotive Technology
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• 제8권3호
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• pp.337-342
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• 2007

A multi-objective optimization technique was implemented to obtain optimal topologies of the inner reinforcement for a vehicle's hood simultaneously considering the static stiffness of bending and torsion and natural frequency. In addition, a smoothing scheme was used to suppress the checkerboard patterns in the ESO method. Two models with different curvature were chosen in order to investigate the effect of curvature on the static stiffness and natural frequency of the inner reinforcement. A scale factor was employed to properly reflect the effect of each objective function. From several combinations of weighting factors, a Pareto-optimal topology solution was obtained. As the weighting factor for the elastic strain efficiency went from 1 to 0, the optimal topologies transmitted from the optimal topology of a static stiffness problem to that of a natural frequency problem. It was also found that the higher curvature model had a larger static stiffness and natural frequency than the lower curvature model. From the results, it is concluded that the ESO method with a smoothing scheme was effectively applied to topology optimization of the inner reinforcement of a vehicle's hood.

• 산업경영시스템학회지
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• 제39권4호
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• pp.137-146
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• 2016

In recent years, business environment is faced with multi uncertainty that have not been suffered in the past. As supply chain is getting expanded and longer, the flow of information, material and production is also being complicated. It is well known that development service industry using application software has various uncertainty in random events such as supply and demand fluctuation of developer's capcity, project effective date after winning a contract, manpower cost (or revenue), subcontract cost (or purchase), and overrun due to developer's skill-level. This study intends to social contribution through attempts to optimize enterprise's goal by supply chain management platform to balance demand and supply and stochastic programming which is basically applied in order to solve uncertainty considering economical and operational risk at solution supplier. In Particular, this study emphasizes to determine allocation of internal and external manpower of developers using S&OP (Sales & Operations Planning) as monthly resource input has constraint on resource's capability that shared in industry or task. This study is to verify how Stochastic Programming such as Markowitz's MV (Mean Variance) model or 2-Stage Recourse Model is flexible and efficient than Deterministic Programming in software enterprise field by experiment with process and data from service industry which is manufacturing software and performing projects. In addition, this study is also to analysis how profit and labor input plan according to scope of uncertainty is changed based on Pareto Optimal, then lastly it is to enumerate limitation of the study extracted drawback which can be happened in real business environment and to contribute direction in future research considering another applicable methodology.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권11호
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• pp.1106-1110
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• 2010

본 논문은 자동화 컨테이너 터미널의 장치장에서 장치 위치 결정 전략을 다목적 진화 알고리즘(MOEA: Multi-Objective Evolutionary Algorithm)을 이용해 최적화하는 방안을 제안한다. 장치장의 해측과 육측 생산성은 서로 상충하기 때문에, 이 둘을 동시에 최대화하는 것은 불가능하다. 대신 본 논문에서는 MOEA를 이용해 파레토 최적해 집합(Pareto optimal set)을 구하였다. 초기 실험 결과 장치장의 컨테이너 점유율이 높은 어려운 문제의 경우, MOEA의 집단이 지역 해에 쉽게 빠지는 것을 확인하였다. 이에 본 논문에서는 난이도가 다른 두 개의 문제를 동시에 최적화함으로써 집단의 다양성을 유지하는 방안을 제안하였으며, 실험 결과 제안 방안이 단일 문제만 해결하는 방안에 비해 동일한 비용으로 더 좋은 전략을 얻을 수 있음을 확인하였다.

• 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.