• Title/Summary/Keyword: Approximation algorithm

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Optimization of Steel Box Girder Bridges using Approximate Reanalysis Technique (재해석 기법을 이용한 강상자형교의 최적설계)

  • Min, Dae-Hong;Yoon, Woo-Hyun;Chung, Jee-Seung;Yang, Sung-Don
    • Journal of the Korean Society of Safety
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    • v.26 no.4
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    • pp.80-86
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    • 2011
  • Structural optimization algorithm of steel box girder bridges using improved higher-order approximate reanalysis technique is proposed in this paper. The proposed approximation method is a generalization of the convex approximation method. The order of the approximate reanalysis for each function is analytically adjusted in the optimization process. This self-adjusted capability makes the approximate structural analysis values conservative enough to maintain the optimum design point of the approximate problem. The efficiency of proposed optimazation algorithm, compared with conventional algorithm, is successfully demonstrated in the steel box girder bridges. The efficiency and robustness of proposed algorithm is also demonstrated in practical steel box girder bridges.

Approximation Algorithms for Scheduling Parallel Jobs with More Machines

  • Kim, Jae-Hoon
    • Journal of information and communication convergence engineering
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    • v.9 no.4
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    • pp.471-474
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    • 2011
  • In parallel job scheduling, each job can be executed simultaneously on multiple machines at a time. Thus in the input instance, a job $J_i$ requires the number $m_i$ of machines on which it shall be processed. The algorithm should determine not only the execution order of jobs but also the machines on which the jobs are executed. In this paper, when the jobs have deadlines, the problem is to maximize the total work of jobs which is completed by their deadlines. The problem is known to be strongly NP-hard [5] and we investigate the approximation algorithms for the problem. We consider a model in which the algorithm can have more machines than the adversary. With this advantage, the problem is how good solution the algorithm can produce against the optimal algorithm.

Sequential Approximate Optimization by Dual Method Based on Two-Point Diagonal Quadratic Approximation (이점 대각 이차 근사화 기법을 쌍대기법에 적용한 순차적 근사 최적설계)

  • Park, Seon-Ho;Jung, Sang-Jin;Jeong, Seung-Hyun;Choi, Dong-Hoon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.35 no.3
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    • pp.259-266
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    • 2011
  • We present a new dual sequential approximate optimization (SAO) algorithm called SD-TDQAO (sequential dual two-point diagonal quadratic approximate optimization). This algorithm solves engineering optimization problems with a nonlinear objective and nonlinear inequality constraints. The two-point diagonal quadratic approximation (TDQA) was originally non-convex and inseparable quadratic approximation in the primal design variable space. To use the dual method, SD-TDQAO uses diagonal quadratic explicit separable approximation; this can easily ensure convexity and separability. An important feature is that the second-derivative terms of the quadratic approximation are approximated by TDQA, which uses only information on the function and the derivative values at two consecutive iteration points. The algorithm will be illustrated using mathematical and topological test problems, and its performance will be compared with that of the MMA algorithm.

Optimum design of shape and size of truss structures via a new approximation method

  • Ahmadvand, Hosein;Habibi, Alireza
    • Structural Engineering and Mechanics
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    • v.76 no.6
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    • pp.799-821
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    • 2020
  • The optimum design of truss structures is one of the significant categories in structural optimization that has widely been applied by researchers. In the present study, new mathematical programming called Consistent Approximation (CONAP) method is utilized for the simultaneous optimization of the size and shape of truss structures. The CONAP algorithm has already been introduced to optimize some structures and functions. In the CONAP algorithm, some important parameters are designed by employing design sensitivities to enhance the capability of the method and its consistency in various optimum design problems, especially structural optimization. The cross-sectional area of the bar elements and the nodal coordinates of the truss are assumed to be the size and shape design variables, respectively. The displacement, allowable stress and the Euler buckling stress are taken as the design constraints for the problem. In the proposed method, the primary optimization problem is replaced with a sequence of explicit sub-problems. Each sub-problem is efficiently solved using the sequential quadratic programming (SQP) algorithm. Several truss structures are designed by employing the CONAP method to illustrate the efficiency of the algorithm for simultaneous shape and size optimization. The optimal solutions are compared with some of the mathematical programming algorithms, the approximation methods and metaheuristic algorithms those reported in the literature. Results demonstrate that the accuracy of the optimization is improved and the convergence rate speeds up.

Routh Approximants with Arbitrary Order

  • 주윤석;김동민
    • ICROS
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    • v.1 no.1
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    • pp.50-50
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    • 1995
  • It has been pointed out in the literature that the Routh approximation method for order reduction has limitations in treating transfer functions with the denominator-numerator order difference not equal to one. The purpose of this paper is to present a new algorithm based on the Routh approximation method that can be applied to general rational transfer functions, yielding reduced models with arbitrary order.

3-D Crosshole EM Modeling by the Extended Born Approximations (확장된 Born근사법에 의한 시추공간 3차원 전자탐사 모델링)

  • Cho, In-Ky;Choi, Kyoung-Hwa
    • Geophysics and Geophysical Exploration
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    • v.2 no.3
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    • pp.142-148
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    • 1999
  • Three-dimensional electromagnetic modeling algorithm in homogeneous half-space was developed using the extended Born approximation to an electric field integral equation. To examine the performance of the extended Born approximation algorithm, the results were compared with those of the full integral equation results. For a crosshole source-receiver configuration, the agreement between the integral equation and the extended Born approximation was remarkable when the source frequency is lower than 20 kHz and conductivity contrast lower than 1:10. Beyond this conductivity contrast, the simulated results by the extended Born approximation exhibit a difference with respect to those by the integral equation. Therefore, the limit of accuracy lies below contrast of 1:10 in the extended Born approximation. Since for the source frequency range from 20 kHz to 100 kHz, however, the difference is relatively small, the extended Born approximation could be used for a reasonable 3-D EM modeling algorithm.

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Building Detection Using Segment Measure Function and Line Relation

  • Ye, Chul-Soo;Kim, Gyeong-Hwan;Lee, Kwae-Hi
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.177-181
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    • 1999
  • This paper presents an algorithm for building detection from aerial image using segment measure function and line relation. In the detection algorithm proposed, edge detection, linear approximation and line linking are used and then line measure function is applied to each line segment in order to improve the accuracy of linear approximation. Parallelisms, orthogonalities are applied to the extracted liner segments to extract building. The algorithm was applied to aerial image and the buildings were accurately detected.

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On A Symbolic Method for Error Estimation of a Mixed Interpolation

  • Thota, Srinivasarao
    • Kyungpook Mathematical Journal
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    • v.58 no.3
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    • pp.453-462
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    • 2018
  • In this paper, we present a symbolic formulation of the error obtained due to an approximation of a given function by the mixed-interpolating function. Using the proposed symbolic method, we compute the error evaluation operator as well as the error estimation at any arbitrary point. We also present an algorithm to compute an approximation of a function by the mixed interpolation technique in terms of projector operator. Certain examples are presented to illustrate the proposed algorithm. Maple implementation of the proposed algorithm is discussed with sample computations.

A Square-Root Forward Backward Correlation-based Projection Approximation for Subspace Tracking (신호부공간 추정 성능 향상을 위한 전후방 상관과 제곱근행렬 갱신을 이용한 COPAST(correlation-based projection approximation for subspace-tracking) 알고리즘 연구)

  • Lim, June-Seok;Pyeon, Yong-Kug
    • 전자공학회논문지 IE
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    • v.48 no.1
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    • pp.7-15
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    • 2011
  • In this paper, we propose a correlation-based subspace estimation technique, which is called square-root forward/backward correlation-based projection approximation subspace tracking(SRFB-COPAST). The SRFB-COPAST utilizes the forward and backward correlation matrix as well as square-root recursive matrix update in projection approximation approach to develop the subspace tracking algorithm. With the projection approximation, the square-root recursive FB-COPAST is presented. The proposed algorithm has the better performance than the recently developed COPAST method.

Convergence of Min-Sum Decoding of LDPC codes under a Gaussian Approximation (MIN-SUM 복호화 알고리즘을 이용한 LDPC 오류정정부호의 성능분석)

  • Heo, Jun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.10C
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    • pp.936-941
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    • 2003
  • Density evolution was developed as a method for computing the capacity of low-density parity-check(LDPC) codes under the sum-product algorithm [1]. Based on the assumption that the passed messages on the belief propagation model can be approximated well by Gaussian random variables, a modified and simplified version of density evolution technique was introduced in [2]. Recently, the min-sum algorithm was applied to the density evolution of LDPC codes as an alternative decoding algorithm in [3]. Next question is how the min-sum algorithm is combined with a Gaussian approximation. In this paper, the capacity of various rate LDPC codes is obtained using the min-sum algorithm combined with the Gaussian approximation, which gives a simplest way of LDPC code analysis. Unlike the sum-product algorithm, the symmetry condition [4] is not maintained in the min-sum algorithm. Therefore, the variance as well as the mean of Gaussian distribution are recursively computed in this analysis. It is also shown that the min-sum threshold under a gaussian approximation is well matched to the simulation results.