• Title/Summary/Keyword: 근사최적화

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Design Optimization of a RC Building Structure using an Approximate Optimization Technique (근사최적화 기법을 이용한 RC 빌딩의 구조 최적설계)

  • Park, Chang-Hyun;Ahn, Hee-Jae;Choi, Dong-Hoon;Jung, Cheul-Kyu
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.24 no.2
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    • pp.223-233
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    • 2011
  • A design optimization problem was formulated to minimize the volume of an RC building structure while satisfying design constraints on structural displacements under vertical, wind and seismic loads. We employed metamodel-based design optimization using design of experiments, metamodeling and optimization algorithm to circumvent the difficulty of the automation of structural analysis procedure. Especially, we proposed a design approach of repetitive design optimizations by stages with changing the side constraint values on design variables and limit values on design constraints until a satisfactory design result was obtained. Using the proposed design approach, the volume of the RC building structure has been reduced by 53.3 % compared to the initial one while satisfying all the design constraints. This design result clearly shows the validity of the proposed design approach.

Point-Based Value Iteration for Constrained POMDPs (제약을 갖는 POMDP를 위한 점-기반 가치 반복 알고리즘)

  • Kim, Dong-Ho;Lee, Jae-Song;Kim, Kee-Eung;Poupart, Pascal
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06a
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    • pp.286-289
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    • 2011
  • 제약을 갖는 부분 관찰 의사결정 과정(Constrained Partially Observable Markov Decision Process; CPOMDP)는 정책이 제약(constraint)를 만족하면서 가치 함수를 최적화하도록 일반적인 부분 관찰 의사결정과정(POMDP)을 확장한 모델이다. CPOMDP는 제한된 자원을 가지거나 여러 개의 목적 함수를 가지는 문제를 자연스럽게 모델링할 수 있기 때문에 일반적인 POMDP에 비해 더 실용적인 장점을 가진다. 본 논문에서는 CPOMDP의 확률적 최적 정책 및 근사 최적 정책을 계산할 수 있는 최적 및 근사 동적 프로그래밍 알고리즘을 제안한다. 최적 알고리즘은 동적 프로그래밍의 각 단계마다 미니맥스 이차 제약 계획 문제를 계산해야 하는 반면에 근사 알고리즘은 선형 계획 문제만을 필요로 하는 점-기반(point-based) 가치 업데이트를 이용한다. 실험 결과, 확률적 정책이 결정적(deterministic) 정책보다 더 나은 성능을 보이며, 근사 알고리즘을 통해 계산 시간을 줄일 수 있음을 보였다.

Design Optimization Using the Two-Point Convex Approximation (이점 볼록 근사화 기법을 적용한 최적설계)

  • Kim, Jong-Rip;Choi, Dong-Hoon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.6
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    • pp.1041-1049
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    • 2003
  • In this paper, a new local two-point approximation method which is based on the exponential intervening variable is proposed. This new algorithm, called the Two-Point Convex Approximation(TPCA), use the function and design sensitivity information from the current and previous design points of the sequential approximate optimization to generate a sequence of convex, separable subproblems. This paper describes the derivation of the parameters associated with the approximation and the numerical solution procedure. In order to show the numerical performance of the proposed method, a sequential approximate optimizer is developed and applied to solve several typical design problems. These optimization results are compared with those of other optimizers. Numerical results obtained from the test examples demonstrate the effectiveness of the proposed method.

A Study on Approximation Query Processing Method Based on Machine Learning Models (머신 러닝 모델 기반 근사 질의 처리 방법에 관한 연구)

  • Park, Choon Seo;Kim, Sung-Soo;Nam, Taek Yong;Lee, Taewhi
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.532-534
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    • 2021
  • 최근 데이터의 양이 급격히 증가함에 따라 빅데이터 환경에서 데이터 질의 처리 수행 시 연산 시간이 많이 소요되는 문제점이 발생한다. 이러한 처리 시간을 줄이기 위한 방법으로 근사질의 처리에 대한 연구의 필요성이 대두되고 있다. 근사 질의 처리 방법은 정확도가 다소 떨어지더라도 빠른 결과를 요구하는 응용 분야에서 매우 유용하게 쓰일 수 있다. 본 논문에서는 사용자가 원하는 결과 정확도와 적시성 등을 지원하기 위한 근사 질의 처리 언어 확장, 실행 계획생성 및 질의 최적화 기술을 제안하고, 설계 방향 및 특징 등에 대해서 설명한다.

Approximation Algorithm for Multi Agents-Multi Tasks Assignment with Completion Probability (작업 완료 확률을 고려한 다수 에이전트-다수 작업 할당의 근사 알고리즘)

  • Kim, Gwang
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.2
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    • pp.61-69
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    • 2022
  • A multi-agent system is a system that aims at achieving the best-coordinated decision based on each agent's local decision. In this paper, we consider a multi agent-multi task assignment problem. Each agent is assigned to only one task and there is a completion probability for performing. The objective is to determine an assignment that maximizes the sum of the completion probabilities for all tasks. The problem, expressed as a non-linear objective function and combinatorial optimization, is NP-hard. It is necessary to design an effective and efficient solution methodology. This paper presents an approximation algorithm using submodularity, which means a marginal gain diminishing, and demonstrates the scalability and robustness of the algorithm in theoretical and experimental ways.

Design Optimization of the Air Bearing Surface for the Optical Flying Bead (Optical Flying Head의 Air Bearing Surface 형상 최적 설계)

  • Lee Jongsoo;Kim Jiwon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.2 s.233
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    • pp.303-310
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    • 2005
  • The systems with probe and SIL(Solid Immersion Lens) mechanisms have been researched as the technology to perform NFR(Near Field Recording). Most of them use the flying head mechanism to accomplish high recording density and fast data transfer rate. In this paper, ABS shape of flying head was optimized with the object of securing the maximum compliance ability of OFH. We suggest low different optimization processes to predict the static flying characteristics for the OFH. Two different approximation methods, regression analysis and back propagation neural network were used. And we compared the result of directly connected(between CAE and optimizer) method and two approximated optimization results. Design Optimization Tool(DOT) and ${\mu}GA$ were used as the optimizers.

Utilizing Soft Computing Techniques in Global Approximate Optimization (전역근사최적화를 위한 소프트컴퓨팅기술의 활용)

  • 이종수;장민성;김승진;김도영
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2000.04b
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    • pp.449-457
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    • 2000
  • The paper describes the study of global approximate optimization utilizing soft computing techniques such as genetic algorithms (GA's), neural networks (NN's), and fuzzy inference systems(FIS). GA's provide the increasing probability of locating a global optimum over the entire design space associated with multimodality and nonlinearity. NN's can be used as a tool for function approximations, a rapid reanalysis model for subsequent use in design optimization. FIS facilitates to handle the quantitative design information under the case where the training data samples are not sufficiently provided or uncertain information is included in design modeling. Properties of soft computing techniques affect the quality of global approximate model. Evolutionary fuzzy modeling (EFM) and adaptive neuro-fuzzy inference system (ANFIS) are briefly introduced for structural optimization problem in this context. The paper presents the success of EFM depends on how optimally the fuzzy membership parameters are selected and how fuzzy rules are generated.

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Die-Speed Optimization in Titanium-Disk Near-Net Shape Hot-Forging (티타늄디스크 근사정형 열간단조시 금형속도의 최적화)

  • 박종진
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.19 no.4
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    • pp.896-907
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    • 1995
  • Titanium 6242(.alpha. + .betha.) alloy has a good strength/weight ratio and is used for aircraft components such as engine disks and compressor blades. When this material is forged at an elevated temperature, the process parameters should be carefully controlled because the process window of this material is quite narrow. In the present investigation, a rigid-thermoviscoplastic finite element method is used to predict the deformation behavior and temperature/strain distributions in an engine disk during near-net shape hot forging. The purpose of the investigation is to obtain a proper ram speed profile, assuming the hydraulic press used in the forging is capable of varying ram speed during loading. In result, it was found that the ram speed at constant strain-rate of 0.5/sec shows a sound deformation behavior, a relatively uniform deformation and a good temperature distribution. This information is also valuable in predicting resulting microstructures in the disk.

HDD Cover FE Model Updating using Multiobjective Optimization (다목적 최적화 기법을 이용한 하드디스크 커버 유한요소 모델개선)

  • 김경호;박윤식
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.05a
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    • pp.565-570
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    • 2001
  • 대상 기계구조물의 유한요소 모델로부터 구한 해석결과가 실험결과와 오차를 나타낼 때, 이러한 오차를 줄일 수 있도록 유한요소 모델의 변경이 요구된다. 유한요소 모델개선은 이러한 역문제(Inverse Problem)를 다루는 체계적인 접근법이다. 일반적으로 유한요소 모델에서 변경할 수 있는 매개변수의 개수는 실험결과의 개수보다 많으므로 실험결과와 일치되는 개선된 유한요소 모델은 무한하다고 할 수 있다. 그러나, 개선된 유한요소 모델이 물리적 타당성을 갖도록 매개변수의 변경량에 제한을 주면 일반적으로 초기 유한요소 모델에 비해 실험결과와의 오차가 개선된 근사해만 존재하게 된다. 따라서, 모델개선 과정을 통해 구한 개선된 모델은 오차의 평가기준 또는 목적함수에 따라 정해진 다양한 근사해 중 하나이다. 기존의 모델개선 방법에서는 단 하나의 오차 평가기준 또는 목적함수를 사용하고 이를 최소화 하는 모델을 구한다. 개선된 모델을 구하기 이전에는 사용된 평가기준이 타당한지 검토할 수 없으므로 대부분의 경우, 시행착오법으로 목적함수를 설정하게 된다. 본 논문에서는 다목적 최적화 기법을 이용한 오차 평가기준을 소개하고 이를 하드디스크커버 유한요소 모델개선에 응용한다.

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Optimization of a Gate Valve using Design of Experiments and the Kriging Based Approximation Model (실험계획법과 크리깅 근사모델에 의한 게이트밸브 최적화)

  • Kang, Jung-Ho;Kang, Jin;Park, Young-Chul
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.14 no.6
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    • pp.125-131
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    • 2005
  • The purpose of this study is an optimization of gate valve made by forging method instead of welding method. In this study, we propose an optimal shape design to improve the mechanical efficiency of gate valve. In order to optimize more efficiently and reliably, the meta-modeling technique has been developed to solve such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Also, we prove reliability of the DACE model's application to gate valve by computer simulations using FEM(Finite Element Method).