• Title/Summary/Keyword: discrete solution

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Local Solution of a Sequential Algorithm Using Orthogonal Arrays in a Discrete Design Space (이산설계공간에서 직교배열표를 이용한 순차적 알고리듬의 국부해)

  • Yi, Jeong-Wook;Park, Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.9
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    • pp.1399-1407
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    • 2004
  • Structural optimization has been carried out in continuous design space or in discrete design space. Generally, available designs are discrete in design practice. However, the methods for discrete variables are extremely expensive in computational cost. An iterative optimization algorithm is proposed for design in a discrete space, which is called a sequential algorithm using orthogonal arrays (SOA). We demonstrate verifying the fact that a local optimum solution can be obtained from the process with this algorithm. The local optimum solution is defined in a discrete design space. Then the search space, which is a set of candidate values of each design variables formed by the neighborhood of a current design point, is defined. It is verified that a local optimum solution can be found by sequentially moving the search space. The SOA algorithm has been applied to problems such as truss type structures. Then it is confirmed that a local solution can be obtained by using the SOA algorithm

Local Solution of Sequential Algorithm Using Orthogonal Arrays in Discrete Design Space (이산설계공간에서 직교배열표를 이용한 순차적 알고리듬의 국부해)

  • Yi, Jeong-Wook;Park, Gyung-Jin
    • Proceedings of the KSME Conference
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    • 2004.04a
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    • pp.1005-1010
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    • 2004
  • The structural optimization has been carried out in the continuous design space or in the discrete design space. Generally, available designs are discrete in design practice. But methods for discrete variables are extremely expensive in computational cost. In order to overcome this weakness, an iterative optimization algorithm was proposed for design in the discrete space, which is called as a sequential algorithm using orthogonal arrays (SOA). We focus to verify the fact that the local solution can be obtained throughout the optimization with this algorithm. The local solution is defined in discrete design space. Then the search space, which is the set of candidate values of each design variables formed by the neighborhood of current design point, is defined. It is verified that a local solution can be founded by moving sequentially the search space. The SOA algorithm has been applied to problems such as truss type structures. Then it is confirmed that a local solution can be obtained using the SOA algorithm

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Global Optimization Using a Sequential Algorithm with Orthogonal Arrays in Discrete Space (이산공간에서 순차적 알고리듬(SOA)을 이용한 전역최적화)

  • Cho, Bum-Sang;Lee, Jeong-Wook;Park, Gyung-Jin
    • Proceedings of the KSME Conference
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    • 2004.11a
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    • pp.858-863
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    • 2004
  • In the optimized design of an actual structure, the design variable should be selected among any certain values or corresponds to a discrete design variable that needs to handle the size of a pre-formatted part. Various algorithms have been developed for discrete design. As recently reported, the sequential algorithm with orthogonal arrays(SOA), which is a local minimum search algorithm in discrete space, has excellent local minimum search ability. It reduces the number of function evaluation using orthogonal arrays. However it only finds a local minimum and the final solution depends on the initial value. In this research, the genetic algorithm, which defines an initial population with the potential solution in a global space, is adopted in SOA. The new algorithm, sequential algorithm with orthogonal arrays and genetic algorithm(SOAGA), can find a global solution with the properties of genetic algorithm and the solution is found rapidly with the characteristics of SOA.

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BOUNDARY POINTWISE ERROR ESTIMATE FOR FINITE ELEMENT METHOD

  • Bae, Hyeong-Ohk;Chu, Jeong-Ho;Choe, Hi-Jun;Kim, Do-Wan
    • Journal of the Korean Mathematical Society
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    • v.36 no.6
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    • pp.1033-1046
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    • 1999
  • This paper is devoted to the point wise error estimate up to boundary for the standard finite element solution of Poisson equation with Dirichlet boundary condition. Our new approach used the discrete maximum principle for the discrete harmonic solution. once the mesh in our domain satisfies the $\beta$-condition defined by us, the discrete harmonic solution with dirichlet boundary condition has the discrete maximum principle and the pointwise error should be bounded by L-errors newly obtained.

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Discrete Sizing Design of Truss Structure Using an Approximate Model and Post-Processing (근사모델과 후처리를 이용한 트러스 구조물의 이산 치수설계)

  • Lee, Kwon-Hee
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.19 no.5
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    • pp.27-37
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    • 2020
  • Structural optimization problems with discrete design variables require more function calculations (or finite element analyses) than those in the continuous design space. In this study, a method to find an optimal solution in the discrete design of the truss structure is presented, reducing the number of function calculations. Because a continuous optimal solution is the Karush-Kuhn-Tucker point that satisfies the optimality condition, it is assumed that the discrete optimal solution is around the continuous optimum. Then, response values such as weight, displacement, and stress are predicted using approximate models-referred to as hybrid metamodels-within specified design ranges. The discrete design method using the hybrid metamodels is used as a post-process of the continuous optimization process. Standard truss design problems of 10-bar, 25-bar, 15-bar, and 52-bar are solved to show the usefulness of this method. The results are compared with those of existing methods.

Simulation Study of Discrete Event Systems using Fast Approximation Method of Single Run and Optimization Method of Multiple Run (단일 실행의 빠른 근사해 기법과 반복 실행의 최적화 기법을 이용한 이산형 시스템의 시뮬레이션 연구)

  • Park, Kyoung Jong;Lee, Young Hae
    • Journal of Korean Institute of Industrial Engineers
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    • v.32 no.1
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    • pp.9-17
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    • 2006
  • This paper deals with a discrete simulation optimization method for designing a complex probabilistic discrete event simulation. The developed algorithm uses the configuration algorithm that can change decision variables and the stopping algorithm that can end simulation in order to satisfy the given objective value during single run. It tries to estimate an auto-regressive model for evaluating correctly the objective function obtained by a small amount of output data. We apply the proposed algorithm to M/M/s model, (s, S) inventory model, and known-function problem. The proposed algorithm can't always guarantee the optimal solution but the method gives an approximate feasible solution in a relatively short time period. We, therefore, show the proposed algorithm can be used as an initial feasible solution of existing optimization methods that need multiple simulation run to search an optimal solution.

Discrete Group Method for Nonlinear Heat Equation

  • Darania, Parviz;Ebadian, Ali
    • Kyungpook Mathematical Journal
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    • v.46 no.3
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    • pp.329-336
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    • 2006
  • In the category of the group theoretic methods using invertible discrete group transformation, we give a useful relation between Emden-Fowler equations and nonlinear heat equation. In this paper, by means of appropriate transformations of discrete group analysis, the nonlinear hate equation transformed into the class of the Emden-Fowler equations. This approach shows that, under the group action, the solution of reference equation can be transformed into the solution of the transformed equation.

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Study on an optimum solution for discrete optimal $H_{\infty}$-control problem (이산 최적 $H_{\infty}$-제어 문제의 최적해를 구하는 방법에 대한 연구)

  • 하철근
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.565-568
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    • 1996
  • In this paper, a solution method is proposed to calculate the optimum solution to discrete optimal H$_{.inf}$ control problem for feedback of linear time-invariant system states and disturbance variable. From the results of this study, condition of existence and uniqueness of its solution is that transfer matrix of controlled variable to input variable is left invertible and has no invariant zeros on the unit circle of the z-domain as well as extra geometric conditions given in this paper. Through a numerical example, the noniterative solution method proposed in this paper is illustrated.

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