• 제목/요약/키워드: parametric search

검색결과 47건 처리시간 0.021초

매개변수 종속 최적화에서 최대치형 목적함수 처리에 관한 연구 (A study on the treatment of a max-value cost function in parametric optimization)

  • 김민수;최동훈
    • 대한기계학회논문집A
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    • 제21권10호
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    • pp.1561-1570
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    • 1997
  • This study explores the treatment of the max-value cost function over a parameter interval in parametric optimization. To avoid the computational burden of the transformation treatment using an artificial variable, a direct treatment of the original max-value cost function is proposed. It is theoretically shown that the transformation treatment results in demanding an additional equality constraint of dual variables as a part of the Kuhn-Tucker necessary conditions. Also, it is demonstrated that the usability and feasibility conditions on the search direction of the transformation treatment retard convergence rate. To investigate numerical performances of both treatments, typical optimization algorithms in ADS are employed to solve a min-max steady-state response optimization. All the algorithm tested reveal that the suggested direct treatment is more efficient and stable than the transformation treatment. Also, the better performing of the direct treatment over the transformation treatment is clearly shown by constrasting the convergence paths in the design space of the sample problem. Six min-max transient response optimization problems are also solved by using both treatments, and the comparisons of the results confirm that the performances of the direct treatment is better than those of the tranformation treatment.

라이다 점군의 효율적 검색을 위한 CUDA 기반 옥트리 알고리듬 구현 (Implementation of CUDA-based Octree Algorithm for Efficient Search for LiDAR Point Cloud)

  • 김형우;이양원
    • 대한원격탐사학회지
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    • 제34권6_1호
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    • pp.1009-1024
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    • 2018
  • 라이다의 활용 증가와 함께 점군 자료의 양이 급증할 것으로 예상되며, 이에 따라 효율적인 점군 검색 및 자료 분석을 위한 차원 축소 방법의 중요성이 강조되고 있다. 이에 따라 본 연구에서는 입력된 원점과 방향 벡터를 이용해 옥트리 노드를 조회하는 파라메트릭 알고리듬의 특징에 따른 기존 CPU, GPU 기반 옥트리의 한계를 정의하고, 이를 극복할 수 있는 검색 기법을 제시한다. GPU 옥트리 환경을 활용할 수 있는 파라메트릭 알고리듬을 구현하고 이에 대한 성능평가를 수행하였으며, 또한 검색된 지점을 활용하여 잡음이 제거된 2차원 영상 투영 방법을 구현하였다.

다품목(多品目) 생산체제(生産體制)의 생산계획(生産計劃)을 위한 모델 (A Model for Production Planning in a Multi-item Production System -Multi-item Parametric Decision Rule-)

  • 최병규
    • 대한산업공학회지
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    • 제1권2호
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    • pp.27-38
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    • 1975
  • This paper explores a quantitative decision-making system for planning production, inventories and work-force in a multi-item production system. The Multi-item Parametric Decision Rule (MPDR) model, which assumes the existence of two types of linear feed-back rules, one for work-force level and one for production rates, is basically an extension of the existing method of Parametric Production Planning (PPP) proposed by C.H. Jones. The MPDR model, however, explicitly considers the effect of manufacturing progress and other factors such as employee turn-over, difference in work-days between month etc., and it also provides decision rules for production rates of individual items. First, the cost relations of the production system are estimated in terms of mathematical functions, and then decision rules for work-force level and production rates of individual items are establised based upon the estimated objective cost function. Finally, a direct search technique is used to find a set of parameters which minimizes the total cost of the objective function over a specified planning horizon, given estimates of future demands and initial values of inventories and work-force level. As a case problem, a hypothetical decision rule is developed for a particular firm (truck assembly factory).

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Complete 3D Surface Reconstruction from Unstructured Point Cloud

  • Kim, Seok-Il;Li, Rixie
    • Journal of Mechanical Science and Technology
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    • 제20권12호
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    • pp.2034-2042
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    • 2006
  • In this study, a complete 3D surface reconstruction method is proposed based on the concept that the vertices, of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out. Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.

Energy Efficiency Resource Allocation for MIMO Cognitive Radio with Multiple Antenna Spectrum Sensing

  • Ning, Bing;Yang, Shouyi;Mu, Xiaomin;Lu, Yanhui;Hao, Wanming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권11호
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    • pp.4387-4404
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    • 2015
  • The energy-efficient design of sensing-based spectrum sharing of a multi-input and multi-output (MIMO) cognitive radio (CR) system with imperfect multiple antenna spectrum sensing is investigated in this study. Optimal resource allocation strategies, including sensing time and power allocation schemes, are studied to maximize the energy efficiency (EE) of the secondary base station under the transmit power and interference power constraints. EE problem is formulated as a nonlinear stochastic fractional programming of a nonconvex optimal problem. The EE problem is transformed into its equivalent nonlinear parametric programming and solved by one-dimension search algorithm. To reduce searching complexity, the search range was founded by demonstration. Furthermore, simulation results confirms that an optimal sensing time exists to maximize EE, and shows that EE is affected by the spectrum detection factors and corresponding constraints.

Optimal stacking sequence design of laminate composite structures using tabu embedded simulated annealing

  • Rama Mohan Rao, A.;Arvind, N.
    • Structural Engineering and Mechanics
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    • 제25권2호
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    • pp.239-268
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    • 2007
  • This paper deals with optimal stacking sequence design of laminate composite structures. The stacking sequence optimisation of laminate composites is formulated as a combinatorial problem and is solved using Simulated Annealing (SA), an algorithm devised based on inspiration of physical process of annealing of solids. The combinatorial constraints are handled using a correction strategy. The SA algorithm is strengthened by embedding Tabu search in order to prevent recycling of recently visited solutions and the resulting algorithm is referred to as tabu embedded simulated Annealing (TSA) algorithm. Computational performance of the proposed TSA algorithm is enhanced through cache-fetch implementation. Numerical experiments have been conducted by considering rectangular composite panels and composite cylindrical shell with different ply numbers and orientations. Numerical studies indicate that the TSA algorithm is quite effective in providing practical designs for lay-up sequence optimisation of laminate composites. The effect of various neighbourhood search algorithms on the convergence characteristics of TSA algorithm is investigated. The sensitiveness of the proposed optimisation algorithm for various parameter settings in simulated annealing is explored through parametric studies. Later, the TSA algorithm is employed for multi-criteria optimisation of hybrid composite cylinders for simultaneously optimising cost as well as weight with constraint on buckling load. The two objectives are initially considered individually and later collectively to solve as a multi-criteria optimisation problem. Finally, the computational efficiency of the TSA based stacking sequence optimisation algorithm has been compared with the genetic algorithm and found to be superior in performance.

A Design of Dynamically Simultaneous Search GA-based Fuzzy Neural Networks: Comparative Analysis and Interpretation

  • Park, Byoung-Jun;Kim, Wook-Dong;Oh, Sung-Kwun
    • Journal of Electrical Engineering and Technology
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    • 제8권3호
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    • pp.621-632
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    • 2013
  • In this paper, we introduce advanced architectures of genetically-oriented Fuzzy Neural Networks (FNNs) based on fuzzy set and fuzzy relation and discuss a comprehensive design methodology. The proposed FNNs are based on 'if-then' rule-based networks with the extended structure of the premise and the consequence parts of the fuzzy rules. We consider two types of the FNNs topologies, called here FSNN and FRNN, depending upon the usage of inputs in the premise of fuzzy rules. Three different type of polynomials function (namely, constant, linear, and quadratic) are used to construct the consequence of the rules. In order to improve the accuracy of FNNs, the structure and the parameters are optimized by making use of genetic algorithms (GAs). We enhance the search capabilities of the GAs by introducing the dynamic variants of genetic optimization. It fully exploits the processing capabilities of the FNNs by supporting their structural and parametric optimization. To evaluate the performance of the proposed FNNs, we exploit a suite of several representative numerical examples and its experimental results are compared with those reported in the previous studies.

조직화되지 않은 점군으로부터의 3차원 완전 형상 복원 (Complete 3D Surface Reconstruction from Unstructured Point Cloud)

  • 이일섭;김석일
    • 대한기계학회논문집A
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    • 제29권4호
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    • pp.570-577
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    • 2005
  • In this study a complete 3D surface reconstruction method is proposed based on the concept that the vertices of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.

개폐식 대공간 구조물의 감쇠장치 적용 및 최적설계에 관한 연구 (Study on Application of Dampers and Optimal Design for Retractable Large Spatial Structures)

  • 정보라;김시욱;김치경
    • 한국전산구조공학회논문집
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    • 제33권6호
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    • pp.351-358
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    • 2020
  • 본 논문는 개폐식 대공간 구조물의 지진하중에 대한 동적응답을 줄이기 위한 목적으로 파라메트릭 설계 기법을 적용한 TMD에 관한 연구이다. 인공지능 알고리즘을 이용하여 감쇠장치의 설치 위치를 자동 탐색하는 컴포넌트를 개발하였다. 이는 구조물의 동적응답을 실시간으로 확인하고, 구조물의 감쇠장치 최적의 위치를 찾을 수 있을 있다. 또한, 여러 대안에 대한 감쇠장치 질량의 최적 값을 찾아주며, 지붕의 열린 상태와 닫힌 상태에 모두 효과적으로 적용될 수 있는 설계안을 찾을 수 있다.

Identification of Fuzzy Inference Systems Using a Multi-objective Space Search Algorithm and Information Granulation

  • Huang, Wei;Oh, Sung-Kwun;Ding, Lixin;Kim, Hyun-Ki;Joo, Su-Chong
    • Journal of Electrical Engineering and Technology
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    • 제6권6호
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    • pp.853-866
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    • 2011
  • We propose a multi-objective space search algorithm (MSSA) and introduce the identification of fuzzy inference systems based on the MSSA and information granulation (IG). The MSSA is a multi-objective optimization algorithm whose search method is associated with the analysis of the solution space. The multi-objective mechanism of MSSA is realized using a non-dominated sorting-based multi-objective strategy. In the identification of the fuzzy inference system, the MSSA is exploited to carry out parametric optimization of the fuzzy model and to achieve its structural optimization. The granulation of information is attained using the C-Means clustering algorithm. The overall optimization of fuzzy inference systems comes in the form of two identification mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and the polynomial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by the MSSA and C-Means, whereas the parameter identification is realized via the MSSA and least squares method. The evaluation of the performance of the proposed model was conducted using three representative numerical examples such as gas furnace, NOx emission process data, and Mackey-Glass time series. The proposed model was also compared with the quality of some "conventional" fuzzy models encountered in the literature.