• Journal of Computational Design and Engineering
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• 제2권3호
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• pp.165-175
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• 2015

One of the current challenges in the domain of the multicriteria shape optimization is to reduce the calculation time required by conventional methods. The high computational cost is due to the high number of simulation or function calls required by these methods. Recently, several studies have been led to overcome this problem by integrating a metamodel in the overall optimization loop. In this paper, we perform a coupling between the Normal Boundary Intersection - NBI - algorithm with Radial Basis Function - RBF - metamodel in order to have a simple tool with a reasonable calculation time to solve multicriteria optimization problems. First, we apply our approach to academic test cases. Then, we validate our method against an industrial case, namely, shape optimization of the bottom of an aerosol can undergoing nonlinear elasto-plastic deformation. Then, in order to select solutions among the Pareto efficient ones, we use the same surrogate approach to implement a method to compute Nash and Kalai-Smorodinsky equilibria.

• 한국자동차공학회논문집
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• 제21권5호
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• pp.8-14
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• 2013

In this study, we propose the method of optimally selecting material of front pillar (A-pillar) and package tray for minimizing weight while satisfying vehicle requirements on static stiffness and dynamic stiffness. First, we formulate a material selection optimization problem. Next, we establish the CAE procedure of evaluating static stiffness and dynamic stiffness. Then, to enhance the efficiency of design work, we integrate and automate the established CAE procedure using a commercial process integration and design optimization (PIDO) tool, PIAnO. For effective optimization, we adopt the approach of metamodel based approximate optimization. As a sampling method, an orthogonal array (OA) is used for selecting sampling points. The response values are evaluated at the sampling points and then these response values are used to generate a metamodel of each response using the radial basis function regression (RBFr). Using the RBFr models, optimization is carried out an evolutionary algorithm that can handle discrete design variables. Material optimization result reveals that the weight is reduced by 49.8% while satisfying all the design constraints.

• 한국융합학회논문지
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• 제10권12호
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• pp.29-34
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• 2019

유전 알고리즘에서 해의 적합도를 계산하는 시간이 오래 걸린다면 메타모델을 만드는 것은 필수적이다. 이에 메타모델의 성능을 높여 유전 알고리즘이 더 좋을 해를 찾게 하기 위한 연구가 진행되어 왔다. 본 연구에서 우리는 이산적인 도메인에서 이산 월시 변환을 사용해 메타모텔의 성능을 높이고자 하였다. 이산 월시 변환을 통해 해의 기저를 변환했고 변환된 해를 사용해 메타모델을 만들었다. 의사-불리언 함수의 대표적인 함수인 NK 모형을 대상으로 실험했고 제안된 모델의 성능에 대한 실증적인 증거를 제공했다. 제안된 모델을 사용해 유전 알고리즘을 수행했을 때, 유전알고리즘이 더 좋은 해를 찾음을 확인했다. 특히, 선행 연구인 유사도 함수를 이산적인 도메인에 적합하게 수정한 방사기저 함수 네트워크보다 좋은 성능을 보였다.

• Journal of Computational Design and Engineering
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• 제3권3호
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• pp.215-225
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• 2016

In recent years, the automotive industry has known a remarkable development in order to satisfy the customer requirements. In this paper, we will study one of the components of the automotive which is the twist beam. The study is focused on the multicriteria design of the automotive twist beam undergoing linear elastic deformation (Hooke's law). Indeed, for the design of this automotive part, there are some criteria to be considered as the rigidity (stiffness) and the resistance to fatigue. Those two criteria are known to be conflicting, therefore, our aim is to identify the Pareto front of this problem. To do this, we used a Normal Boundary Intersection (NBI) algorithm coupling with a radial basis function (RBF) metamodel in order to reduce the high calculation time needed for solving the multicriteria design problem. Otherwise, we used the free form deformation (FFD) technique for the generation of the 3D shapes of the automotive part studied during the optimization process.