• 제목/요약/키워드: Optimization problems

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SIMP 기반 절점밀도법에 의한 3 차원 위상최적화 (3-D Topology Optimization by a Nodal Density Method Based on a SIMP Algorithm)

  • 김철;팡난
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회A
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    • pp.412-417
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    • 2008
  • In a traditional topology optimization method, material properties are usually distributed by finite element density and visualized by a gray level image. The distribution method based on element density is adequate for a great mass of 2-D topology optimization problems. However, when it is used for 3-D topology optimization, it is always difficult to obtain a smooth model representation, and easily appears a virtualconnect phenomenon especially in a low-density domain. The 3-D structural topology optimization method has been developed using the node density instead of the element density that is based on SIMP (solid isotropic microstructure with penalization) algorithm. A computer code based on Matlab was written to validate the proposed method. When it was compared to the element density as design variable, this method could get a more uniform density distribution. To show the usefulness of this method, several typical examples of structure topology optimization are presented.

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One-Sided Optimal Assignment and Swap Algorithm for Two-Sided Optimization of Assignment Problem

  • Lee, Sang-Un
    • 한국컴퓨터정보학회논문지
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    • 제20권12호
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    • pp.75-82
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    • 2015
  • Generally, the optimal solution of assignment problem can be obtained by Hungarian algorithm of two-sided optimization with time complexity $O(n^4)$. This paper suggests one-sided optimal assignment and swap optimization algorithm with time complexity $O(n^2)$ can be achieve the goal of two-sided optimization. This algorithm selects the minimum cost for each row, and reassigns over-assigned to under-assigned cell. Next, that verifies the existence of swap optimization candidates, and swap optimizes with ${\kappa}-opt({\kappa}=2,3)$. For 27 experimental data, the swap-optimization performs only 22% of data, and 78% of data can be get the two-sided optimal result through one-sided optimal result. Also, that can be improves on the solution of best known solution for partial problems.

A new PSRO algorithm for frequency constraint truss shape and size optimization

  • Kaveh, A.;Zolghadr, A.
    • Structural Engineering and Mechanics
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    • 제52권3호
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    • pp.445-468
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    • 2014
  • In this paper a new particle swarm ray optimization algorithm is proposed for truss shape and size optimization with natural frequency constraints. These problems are believed to represent nonlinear and non-convex search spaces with several local optima and therefore are suitable for examining the capabilities of new algorithms. The proposed algorithm can be viewed as a hybridization of Particle Swarm Optimization (PSO) and the recently proposed Ray Optimization (RO) algorithms. In fact the exploration capabilities of the PSO are tried to be promoted using some concepts of the RO. Five numerical examples are examined in order to inspect the viability of the proposed algorithm. The results are compared with those of the PSO and some other existing algorithms. It is shown that the proposed algorithm obtains lighter structures in comparison to other methods most of the time. As will be discussed, the algorithm's performance can be attributed to its appropriate exploration/exploitation balance.

Water Flowing and Shaking Optimization

  • Jung, Sung-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제12권2호
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    • pp.173-180
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    • 2012
  • This paper proposes a novel optimization algorithm inspired by water flowing and shaking behaviors in a vessel. Water drops in our algorithm flow to the gradient descent direction and are sometimes shaken for getting out of local optimum areas when most water drops fall in local optimum areas. These flowing and shaking operations allow our algorithm to quickly approach to the global optimum without staying in local optimum areas. We experimented our algorithm with four function optimization problems and compared its results with those of particle swarm optimization. Experimental results showed that our algorithm is superior to the particle swarm optimization algorithm in terms of the speed and success ratio of finding the global optimum.

CUDA를 이용한 Particle Swarm Optimization 구현 (Implementation of Particle Swarm Optimization Method Using CUDA)

  • 김조환;김은수;김종욱
    • 전기학회논문지
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    • 제58권5호
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    • pp.1019-1024
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    • 2009
  • In this paper, particle swarm optimization(PSO) is newly implemented by CUDA(Compute Unified Device Architecture) and is applied to function optimization with several benchmark functions. CUDA is not CPU but GPU(Graphic Processing Unit) that resolves complex computing problems using parallel processing capacities. In addition, CUDA helps one to develop GPU softwares conveniently. Compared with the optimization result of PSO executed on a general CPU, CUDA saves about 38% of PSO running time as average, which implies that CUDA is a promising frame for real-time optimization and control.

GLOBAL CONVERGENCE OF AN EFFICIENT HYBRID CONJUGATE GRADIENT METHOD FOR UNCONSTRAINED OPTIMIZATION

  • Liu, Jinkui;Du, Xianglin
    • 대한수학회보
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    • 제50권1호
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    • pp.73-81
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    • 2013
  • In this paper, an efficient hybrid nonlinear conjugate gradient method is proposed to solve general unconstrained optimization problems on the basis of CD method [2] and DY method [5], which possess the following property: the sufficient descent property holds without any line search. Under the Wolfe line search conditions, we proved the global convergence of the hybrid method for general nonconvex functions. The numerical results show that the hybrid method is especially efficient for the given test problems, and it can be widely used in scientific and engineering computation.

영역 제거법의 확장을 통한 전체 최적화 알고리듬 개선 (A Global Optimization Algorithm Based on the Extended Domain Elimination Method)

  • 오승환;이병채
    • 대한기계학회논문집A
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    • 제24권1호
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    • pp.240-249
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    • 2000
  • An improved global optimization algorithm is developed by extending the domain elimination method. The concept of triangular patch consists of two or more trajectories of local minimizations is introduced to widen the attraction region of the domain elimination method. Using the an-]c between each of three vertices of the patch and a design point, we measure the proximity, between the design point and the patch. With the Gram-Schimidt orthonormalization, this method can be extended to general n-dimensional problems. We code the original domain elimination algorithm and a patch-based algorithm. Then we compare the performance of two algorithms. Through the well-known example problems. the algorithm using patch is shown to be superior to the original domain elimination algorithm in view of computational efficiency.

비지배 방향정보를 이용한 새로운 다목적 진화 알고리즘 (A New evolutionary Multiobjective Optimization Algorithm based on the Non-domination Direction Information)

  • Kang, Young-Hoon;Zeungnam Bien
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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    • pp.103-106
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    • 2000
  • In this paper, we introduce a new evolutionary multiobjective optimization algorithm based on the non-domination direction information, which can be an alternative among several multiobjective evolutionary algorithms. The new evolutionary multiobjective optimization algorithm proposed in this paper will not use the conventional recombination or mutation operators but use the non-domination directions, which are extracted from the non-domination relation among the population. And the problems of the modified sharing algorithms are pointed out and a new sharing algorithm sill be proposed to overcome those problems.

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DC 모터 파라메터 변동에 대한 면역 알고리즘 제어기 설계 (Immune Algorithm Controller Design of DC Motor with parameters variation)

  • 박진현;전향식;이민중;김현식;최영규
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2002년도 춘계학술대회 및 임시총회
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    • pp.175-178
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    • 2002
  • The proposed immune algorithm has an uncomplicated structure and memory-cell mechanism as the optimization algorithm which imitates the principle of humoral immune response, and has been used as methods to solve parameter optimization problems. Up to now, the applications of immune algorithm have been optimization problems with non-varying system parameters. Therefore, the effect of memory-cell mechanism, which is a merit of immune algorithm, is without. this paper proposes the immune algorithm using a memory-cell mechanism which can be the application of system with nonlinear varying parameters. To verified performance of the proposed immune algorithm, the speed control of nonlinear DC motor are performed. Computer simulation studies show that the proposed immune algorithm has a fast convergence speed and a good control performances under the varying system parameters.

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크랭크 샤프트강재의 마찰용접 최적화와 AE 실시간 평가 (Optimization of Friction Welding for Crank Shaft Steels and Its Real Time AE Evaluation)

  • 오세규;최혜영;공유식
    • 한국해양공학회지
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    • 제13권4호통권35호
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    • pp.98-104
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    • 1999
  • The crank shafts need anti-corrosion materials. So STS 304 is the essential material to manufacture this shaft. However, it costs more to manufacture the shafts by using only STS 304 than welding of STS 304 to other carbon steels. And it has been difficult to weld this sort of dissimilar materials. They could be unstable in the quality by the conventional arc welding. And also they have a lot of technical problems in manufacturing. But by the friction welding technique, it will be able to be made without such problems. Then, this study aimed not only to develop the optimization of dissimilar friction welding of crank shafts steels of STS 304, SM35C, but also to develop the application technique of the acoustic emission to accomplish in-process real-time quality(such as tensile) evaluation during friction welding of the shafts by the AE technique.

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