• 한국지진공학회논문집
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• 제14권2호
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• pp.1-13
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• 2010

본 논문에서는 비선형 지진격리교량의 최적 설계 방법을 제시하였다. 최적설계를 위한 목적함수로는 교각과 지진격리장치의 파괴확률을 고려하였으며, 상충하는 두 목적함수를 동시에 최적화하는 다수의 해를 효율적으로 검색하고자 유전자 알고리즘에 기반한 다목적 최적화기법을 도입하였다. 또한, 최적화 과정에서 요구되는 다수의 비선형 시간이력해석을 수행하지 않고도 교량의 확률적 응답을 효율적으로 예측할 수 있는 추계학적 선형화 방법을 접목하였다. 제시하는 방법의 효율성을 검증하기 위한 수치 예로서 실제 교량인 남한강교를 고려하였고, 제안하는 방법과 기존 비선형 시간이력해석을 이용한 생애주기비용 기반 설계법을 각각 적용하여 내진성능을 비교하였다. 내진성능을 비교한 결과, 제시하는 방법이 기존의 비용에 기반한 최적설계보다 우수한 성능 및 경제성을 보임을 검증하였다. 또한, 다양한 지진하중에 대해서도 제안된 방법이 보다 개선된 성능을 보임을 확인하였다.

• 한국정밀공학회지
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• 제28권4호
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• pp.482-489
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• 2011

In practical design process, designer needs to find an optimal solution by using full factorial discrete combination, rather than by using optimization algorithm considering continuous design variables. So, ANOVA(Analysis of Variance) based on an orthogonal array, i.e. Taguchi method, has been widely used in most parts of industry area. However, the Taguchi method is limited for the shape optimization by using CAE, because the multi-level and multi-objective optimization can't be carried out simultaneously. In this study, a combined method was proposed taking into account of multi-level computational orthogonal array and TOPSIS(Technique for Order preference by Similarity to Ideal Solution), which is known as a classical method of multiple attribute decision making and enables to solve various decision making or selection problems in an aspect of multi-objective optimization. The proposed method was applied to a case study of the multi-level shape optimization of lower arm used to automobile parts, and the design space was explored via an efficient application of the related CAE tools. The multi-level shape optimization was performed sequentially by applying both of the neural network model generated from seven-level four-factor computational orthogonal array and the TOPSIS. The weight and maximum stress of the lower arm, as the objective functions for the multi-level shape optimization, showed an improvement of 0.07% and 17.89%, respectively. In addition, the number of CAE carried out for the shape optimization was only 55 times in comparison to full factorial method necessary to 2,401 times.

• 한국강구조학회 논문집
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• 제14권3호
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• pp.395-402
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• 2002

본 연구는 강상판교량의 합리적인 설계를 위한 다목적 최적설계 방법을 제안하였다. 다목적 최적설계 방법은 기존의 제작비용만을 목적함수로 사용하는 최적설계와는 달리 제작비용과 처짐을 동시에 고려함으로써 보다 합리적인 설계를 유도하고자 하였다. 강상판교량은 많은 부재를 가지고 있고 구조거동이 복잡한 이유로 기존의 최적설계 알고리즘을 이용하면 매우 비효율적이다. 따라서, 매우 효율적인 다단계 최적설계를 이용하였다. 강상판교량의 합리적이고 경제적인 설계를 위해 최적의 제작비용과 처짐과의 관계를 파레토 곡선으로 표현하고 이를 이용하여 합리적인 설계 수준을 정하는 척도로 사용하였다. 이러한 방법은 기존의 단일목적 최적설계에 비해 매우 합리적인 설계결과를 얻을 수 있었다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 춘계학술대회 논문집
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• pp.621-624
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• 2002

The purpose of this paper is a study on getting proper gain set of PID controller which satisfies multi-performance specifications of the control system. The multi-objective optimization method is introduced to evaluate specifications, and the genetic algorithm is used as an optimal problem solver. To enhance the performance of genetic algorithm itself, adaptive technique is included. According to the proposed method in this paper, finding suitable gain set can be more easily accomplishable than manual gain seeking and tuning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5489-5511
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• 2019

The performance of evolutionary algorithms can be seriously weakened when constraints limit the feasible region of the search space. In this paper we present a constrained multi-objective optimization algorithm based on adaptive ε-truncation (ε-T-CMOA) to further improve distribution and convergence of the obtained solutions. First of all, as a novel constraint handling technique, ε-truncation technique keeps an effective balance between feasible solutions and infeasible solutions by permitting some excellent infeasible solutions with good objective value and low constraint violation to take part in the evolution, so diversity is improved, and convergence is also coordinated. Next, an exponential variation is introduced after differential mutation and crossover to boost the local exploitation ability. At last, the improved crowding density method only selects some Pareto solutions and near solutions to join in calculation, thus it can evaluate the distribution more accurately. The comparative results with other state-of-the-art algorithms show that ε-T-CMOA is more diverse than the other algorithms and it gains better in terms of convergence in some extent.

• International Journal of Naval Architecture and Ocean Engineering
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• 제10권4호
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• pp.439-449
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• 2018

In this paper, multi-objective optimization of a multi-bubble pressure cabin in the underwater glider with Blended-Wing-Body (BWB) is carried out using Kriging and the Non-dominated Sorting Genetic Algorithm (NSGA-II). Two objective functions are considered: buoyancy-weight ratio and internal volume. Multi-bubble pressure cabin has a strong compressive capacity, and makes full use of the fuselage space. Parametric modeling of the multi-bubble pressure cabin structure is automatic generated using UG secondary development. Finite Element Analysis (FEA) is employed to study the structural performance using the commercial software ANSYS. The weight of the primary structure is determined from the volume of the Finite Element Structure (FES). The stress limit is taken into account as the constraint condition. Finally, Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) method is used to find some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. The best solution is compared with the initial design results to prove the efficiency and applicability of this optimization method.

• 설비공학논문집
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• 제17권10호
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• pp.938-946
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• 2005

Shape optimization of internally finned circular tube has been peformed for periodically fully developed turbulent flow and heat transfer. The physical domain considered in this study is very complicated due to periodic boundary conditions both streamwise and circumferential directions. Therefore, Pareto frontier sets of a heat exchanger can be acquired by coupling the CFD and the multi-objective genetic algorithm, which is a global optimization technique. The optimal values of fin widths $(d_1,\;d_2)$ and fin height (H) are numerically obtained by minimizing the pressure loss and maximizing the heat transfer rate within ranges of $d_1=0.2\sim1.5\;mm,\;d_2=0.2\sun1.5\;mm,\;and\;H=0.2\sim1.5\;mm$. The optimal values of the design variables are acquired after the fifth generation and also compared to those of a local optimization algorithm for the same geometry and conditions.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.3080-3085
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• 2007

Shape optimization of the 3-dimensional WIG airfoil with 3.0-aspect ratio has been performed by using the multi-objective genetic algorithm. The WIG ship effectively floating above the surface by the ram effect and the virtual additional aspect ratio by a ground is one of next-generation and cost-effective transportations. Unlike the airplane flying out of the ground effect, a WIG ship has possibility to capsize because of unsatisfying the static stability. The WIG ship should satisfy aerodynamic properties as well as a static stability. They tend to strong contradict and it is difficult to satisfy aerodynamic properties and static stability simultaneously. It is inevitable that lift force has to scarify to obtain a static stability. Multi-objective optimization technique that the individual objectives are considered separately instead of weighting can overcome the conflict. Due to handling individual objectives, the optimum cannot be unique but a set of nondominated potential solutions: pareto optimum. There are three objectives; lift coefficient, lift-to-drag ratio and static stability. After a few evolutions, the non-dominated pareto individuals can be obtained. Pareto sets are all the set of possible and excellent solution across the design space. At any selections of the pareto set, these are no better solutions in all design space

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 춘계학술대회논문집
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• pp.113-116
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• 2008

This work presents numerical optimization for design of staggered arrays of dimples printed on opposite surfaces of a cooling channel with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by three non-dimensional geometric design variables composed of dimpled channel height, dimple print diameter, dimple spacing and dimple depth to maximize heat transfer rate compromising with pressure drop. Twenty designs generated by Latin hypercube sampling were evaluated by Reynolds-averaged Navier-Stokes solver and the evaluated objectives were used to construct Pareto optimal front through hybrid multi-objective evolutionary algorithm. The optimum designs were grouped by k-mean clustering technique and some of the clustered points were evaluated by flow analysis. With increase in dimple depth, heat transfer rate increases and at the same time pressure drop also increases, while opposite behavior is obtained for the dimple spacing. The heat transfer performance is related to the vertical motion of the flow and the reattachment length in the dimple.

• 대한기계학회논문집A
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• 제35권7호
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• pp.729-736
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• 2011

TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)는 상충되는 다수의 속성이 존재하는 상황에서 의사결정이 요구되는 다속성 의사결정법(Multi Attribute Decision Making) 중 하나이다. 이는 선택된 대체안이 최선의 이상적 대체안으로부터 가장 가까운 거리에 위치해야 하고, 동시에 부정적으로 이상적인 대체안으로부터는 가장 멀리 위치해야 한다는 논리에 입각한 의사결정 기법이다. TOPSIS 는 최소화와 최대화가 공존하는 다목적함수 형상 최적설계에 적용이 가능하다. 본 연구에서는 TOPSIS 와 베지어 곡선(Rational Bezier Curve)을 적용하여 CRT(Cathode Ray Tubes) 후면유리의 다중목적 형상최적설계를 수행하였다. 무게와 1 차 주응력의 두 가지 다중목적 함수를 최적화하기 위하여, 다중목적 함수의 성능지표를 TOPSIS 의 상대적 근접도로 정의하고 이를 반응표면모델로 구성하여 다중목적 형상최적설계가 가능한 방법론을 제안하였다. 이를 통해 하나의 최적해가 아닌 최적해의 군이 선정되어, 무게와 주응력 최적해의 모순관계를 확인하면서 다양한 설계요구 스펙을 만족시켜줄 수 있는 방안을 설계자가 스스로 선택하도록 하였다.