• International Journal of Naval Architecture and Ocean Engineering
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• 제9권4호
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• pp.373-381
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• 2017

A Collaborative Optimization (CO) methodology for ring-stiffened composite material pressure hull of underwater vehicle is proposed. Structural stability and material strength are both examined. Lamination parameters of laminated plates are introduced to improve the optimization efficiency. Approximation models are established based on the Ellipsoidal Basis Function (EBF) neural network to replace the finite element analysis in layout optimizers. On the basis of a two-level optimization, the simultaneous structure material collaborative optimization for the pressure vessel is implemented. The optimal configuration of metal liner and frames and composite material is obtained with the comprehensive consideration of structure and material performances. The weight of the composite pressure hull decreases by 30.3% after optimization and the validation is carried out. Collaborative optimization based on the lamination parameters can optimize the composite pressure hull effectively, as well as provide a solution for low efficiency and non-convergence of direct optimization with design variables.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2001년도 가을 학술발표회 논문집
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• pp.201-210
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• 2001

In this study, large-scale distributed design approach for a life cycle cost (LCC) optimization of steel box girder bridges was implemented. A collaborative optimization approach is one of the multidisciplinary design optimization approaches and it has been proven to be best suited for distributed design environment. The problem of optimum LCC design of steel box girder bridges is formulated as that of minimization of the expected total LCC that consists of initial cost maintenance cost expected retrofit costs for strength, deflection and crack. To discuss the possibility of the application for the collaborative optimization of steel box girder bridges, the results of this algorithm are compared with those of single level algorithm. From the numerical investigations, the collaborative optimization approach proposed in this study may be expected to be new concepts and design methodologies associated with the LCC approach.

• 한국CDE학회논문집
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• 제5권3호
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• pp.263-275
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• 2000

Multidisciplinary design optimization(MDO) can yield optimal design considering all the disciplinary requirements concurrently. A method to implement the collaborative optimization(CO) approach, one of the MDO methodologies, is developed using a pre-compiler “EzpreCompiler”, a design optimization library “EzOptimizer”, and a common object request broker architecture(CORBA) in distributed computing environment. The CO approach is applied to a mathematical example to show its applicability and equivalence to standard optimization(SO) formulation. In a realistic engineering problem such as optimal design of a two-member hub frame, optimal design of a speed reducer and initial design of a bulk carrier, the CO yields better results than the SO. Furthermore, the CO allows the distributed processing using the CORBA, which leads to reduction of overall computation time.

• 한국항공우주학회지
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• 제43권6호
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• pp.568-583
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• 2015

본 논문에서는 다분야 통합 설계최적화(MDO : Multidisciplinary Design Optimization)를 적용한 지구관측위성의 개념설계 과정 및 결과를 기술하였다. 현재까지 구축된 지구관측 위성의 데이터베이스를 기반으로 주요 파라미터에 대한 개념설계식을 정립하였으며, 다분야 통합 최적설계 아키텍처 중 CO(Collaborative Optimization) 기반을 이용하여 지구관측 위성 시스템의 최적 개념설계를 수행할 수 있는 설계 도구를 개발하였다. 주어진 제약조건을 만족시키면서 위성의 총 질량을 최소화하는 것을 설계 목표로 설정하였으며, 최적화 알고리즘으로는 SQP(Sequential Quadratic Programming)를 이용하였다. 다분야 통합 최적설계를 적용한 개념설계 결과와 ASNARO-1 및 IKONOS-2 위성 규격의 비교를 통해 해당설계도구의 유용성을 검증하였다.

• Journal of Ship and Ocean Technology
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• 제8권2호
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• pp.41-60
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• 2004

Ship design process requires lots of complicated analyses for determining a large number of design variables. Due to its complexity, the process is divided into several tractable designs or analysis problems. The interdependent relationship requires repetitive works. This paper employs collaborative optimization (CO), one of the multidisciplinary design optimization (MDO) techniques, for treating such complex relationship. CO guarantees disciplinary autonomy while maintaining interdisciplinary compatibility due to its bi-level optimization structure. However, the considerably increased computational time and the slow convergence have been reported as its drawbacks. This paper proposes the use of an approximation model in place of the disciplinary optimization in the system-level optimization. Neural network classification is employed as a classifier to determine whether a design point is feasible or not. Kriging is also combined with the classification to make up for the weakness that the classification cannot estimate the degree of infeasibility. For the purpose of enhancing the accuracy of a predicted optimum and reducing the required number of disciplinary optimizations, an approximation management framework is also employed in the system-level optimization.

• Nuclear Engineering and Technology
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• 제55권8호
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• pp.2723-2733
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• 2023

Transuranic nuclides (such as ²³⁸Pu, ²⁵²Cf, ²⁴⁹Bk, etc.) have a wide range of application in industry, medicine, agriculture, and other fields. However, due to the complex conversion chain and remarkable fission losses in the process of transuranic nuclides production, the generation amounts are extremely low. High flux reactor with high neutron flux and flexible irradiation channels, is regarded as the promising candidate for producing transuranic nuclides. It is of great significance to increase the conversion ratio of transuranic nuclides, resulting in higher efficiency and better economy. In this paper, we perform an optimization design evaluation of producing transuranic nuclides in high flux reactor, which includes optimization design of irradiation target and influence study of reactor core loading. It is demonstrated that the production rate increases with appropriately determined target material and target structure. The target loading scheme in the irradiation channel also has a significant influence on the production of transuranic nuclides.

• Journal of Mechanical Science and Technology
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• 제20권1호
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• pp.133-146
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• 2006

Collaborative optimization (CO) is a multi-level decomposed methodology for a large-scale multidisciplinary design optimization (MDO). CO is known to have computational and organizational advantages. Its decomposed architecture removes a necessity of direct communication among disciplines, guaranteeing their autonomy. However, CO has several problems at convergence characteristics and computation time. In this study, such features are discussed and some suggestions are made to improve the performance of CO. Only for the system level optimization, genetic algorithm is used and gradient-based method is used for subspace optimizers. Moreover, response surface models are replaced as analyses in subspaces. In this manner, CO is applied to aero-structural design problems of the aircraft wing and its results are compared with the multidisciplinary feasible (MDF) method and the original CO. Through these results, it is verified that the suggested approach improves convergence characteristics and offers a proper solution.

• 한국인터넷방송통신학회논문지
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• 제18권1호
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• pp.173-183
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• 2018

다자간 협업이 요구되는 신규 사업 시 협업 절차를 수립하거나 이미 다자간 상호 연계 형태로 진행되는 협업 절차에서 문제점을 분석하여 객관적으로 증빙하고 제도를 개정하는 일은 매우 어려운 작업이다. 본 연구에서는 PERT/CPM 네트워크 다이어그램을 활용하여 협업 주체 간 업무 처리 절차를 수립하고 처리 소요 기간을 산출할 수 있는 협업 프로세스를 위한 최적화 수립 모형을 제안하였다. 또한 본 연구에서 개발한 협업 프로세스 최적화 수립 모형의 실효성과 유용성을 검증하기 위하여 고용노동부에서 실시하고 있는 학위연계형 일학습병행제 학습근로자 선발 절차의 협업 절차 최적화 작업에 적용하였다. 본 연구는 협업 절차를 새로이 수립하거나 재구성해야 하는 경우 뿐만 아니라 정보시스템 구축을 위해 협업 주체 간 정보시스템 간 연계 업무 절차를 표준화하기 위하여 유용하게 활용할 수 있다.

• 유통과학연구
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• 제16권2호
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• pp.19-24
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• 2018

Purpose - Drone delivery is expected to revolutionize the supply chain industry. This paper aims to introduce a collaborative parcel delivery problem by truck and drone (hereinafter called "TDRP") and propose a novel heuristic method to solve the problem. Research design, data, and methodology - To show the effectiveness of collaborative delivery by truck and drone, we generate a toy problem composed of 9 customers and the speed of drone is assumed to be two times faster than truck. We compared the delivery completion times by 'truck only' case and 'truck and drone' case by solving the optimization problem respectively. Results - We provide literature reviews for truck and drone routing problem for collaborative delivery and propose a novel and original heuristic method to solve the problem with numerical example. By numerical example, collaborative delivery is expected to reduce delivery completion time by 12~33% than 'truck only' case. Conclusions - In this paper, we introduce the TDRP in order for collaborative delivery to be effective and propose a novel and original heuristic method to solve the problem. The results of research will be help to develop effective heuristic solution and optimize the parcel delivery by using drone.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 추계학술대회논문집A
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• pp.818-823
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• 2000

In practical design studies, most of designers solve multidisciplinary problems with complex design structure. These multidisciplinary problems have hundreds of analysis and thousands of variables. The sequence of process to solve these problems affects the speed of total design cycle. Thus it is very important for designer to reorder original design processes to minimize total cost and time. This is accomplished by decomposing large multidisciplinary problem into several multidisciplinary analysis subsystem (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problem to raise design efficiency by using genetic algorithm and shows the relationship between decomposition and multidisciplinary design optimization (MDO) methodology.