• Title/Summary/Keyword: approximate optimal solution

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SMOOTHING APPROXIMATION TO l1 EXACT PENALTY FUNCTION FOR CONSTRAINED OPTIMIZATION PROBLEMS

  • BINH, NGUYEN THANH
    • Journal of applied mathematics & informatics
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    • v.33 no.3_4
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    • pp.387-399
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    • 2015
  • In this paper, a new smoothing approximation to the l1 exact penalty function for constrained optimization problems (COP) is presented. It is shown that an optimal solution to the smoothing penalty optimization problem is an approximate optimal solution to the original optimization problem. Based on the smoothing penalty function, an algorithm is presented to solve COP, with its convergence under some conditions proved. Numerical examples illustrate that this algorithm is efficient in solving COP.

AN APPROXIMATE ALTERNATING LINEARIZATION DECOMPOSITION METHOD

  • Li, Dan;Pang, Li-Ping;Xia, Zun-Quan
    • Journal of applied mathematics & informatics
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    • v.28 no.5_6
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    • pp.1249-1262
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    • 2010
  • An approximate alternating linearization decomposition method, for minimizing the sum of two convex functions with some separable structures, is presented in this paper. It can be viewed as an extension of the method with exact solutions proposed by Kiwiel, Rosa and Ruszczynski(1999). In this paper we use inexact optimal solutions instead of the exact ones that are not easily computed to construct the linear models and get the inexact solutions of both subproblems, and also we prove that the inexact optimal solution tends to proximal point, i.e., the inexact optimal solution tends to optimal solution.

AN APPROACH FOR SOLVING NONLINEAR PROGRAMMING PROBLEMS

  • Basirzadeh, H.;Kamyad, A.V.;Effati, S.
    • Journal of applied mathematics & informatics
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    • v.9 no.2
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    • pp.717-730
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    • 2002
  • In this paper we use measure theory to solve a wide range of the nonlinear programming problems. First, we transform a nonlinear programming problem to a classical optimal control problem with no restriction on states and controls. The new problem is modified into one consisting of the minimization of a special linear functional over a set of Radon measures; then we obtain an optimal measure corresponding to functional problem which is then approximated by a finite combination of atomic measures and the problem converted approximately to a finite-dimensional linear programming. Then by the solution of the linear programming problem we obtain the approximate optimal control and then, by the solution of the latter problem we obtain an approximate solution for the original problem. Furthermore, we obtain the path from the initial point to the admissible solution.

A Validation Method for Solution of Nonlinear Differential Equations: Construction of Exact Solutions Neighboring Approximate Solutions

  • Lee, Sang-Chul
    • International Journal of Aeronautical and Space Sciences
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    • v.3 no.2
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    • pp.46-58
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    • 2002
  • An inverse method is introduced to construct benchmark problems for the numerical solution of initial value problems. Benchmark problems constructed through this method have a known exact solution, even though analytical solutions are generally not obtainable. The solution is constructed such that it lies near a given approximate numerical solution, and therefore the special case solution can be generated in a versatile and physically meaningful fashion and can serve as a benchmark problem to validate approximate solution methods. A smooth interpolation of the approximate solution is forced to exactly satisfy the differential equation by analytically deriving a small forcing function to absorb all of the errors in the interpolated approximate solution. A multi-variable orthogonal function expansion method and computer symbol manipulation are successfully used for this process. Using this special case exact solution, it is possible to directly investigate the relationship between global errors of a candidate numerical solution process and the associated tuning parameters for a given code and a given problem. Under the assumption that the original differential equation is well-posed with respect to the small perturbations, we thereby obtain valuable information about the optimal choice of the tuning parameters and the achievable accuracy of the numerical solution. Illustrative examples show the utility of this method not only for the ordinary differential equations (ODEs) but for the partial differential equations (PDEs).

A Study on the Error Analysis of the Numerical Solution using Inverse Method (역해석 기법을 이용한 수치해의 오차 분석 연구)

  • Yang, Sung-Wook;Lee, Sang-Chul
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.16 no.2
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    • pp.21-27
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    • 2008
  • An inverse method is introduced to construct the problem for the error analysis of the numerical solution of initial value problem. These problems constructed through this method have a known exact solution, even though analytical solutions are generally not obtainable. The process leading to the exact solution makes use of an initially available approximate numerical solution. A smooth interpolation of the approximate solution is forced to exactly satisfy the differential equation by analytically deriving a small forcing function to absorb all of the errors in the interpolated approximate solution. Using this special case exact solution, it is possible to investigate the relationship between global errors of a candidate numerical solution process and the associated tuning parameters for a given problem. Under the assumption that the original differential equation is well-posed with respect to the small perturbations, we thereby obtain valuable information about the optimal choice of the tuning parameters and the achievable accuracy of the numerical solution.

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Approximate Optimization Design Considering Automotive Wheel Stress (자동차용 휠의 응력을 고려한 근사 최적 설계)

  • Lee, Hyunseok;Lee, Jongsoo
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.24 no.3
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    • pp.302-307
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    • 2015
  • The automobile is an important means of transportation. For this reason, the automotive wheel is also an important component in the automotive industry because it acts as a load support and is closely related to safety. Thus, the wheel design is a very important safety aspect. In this paper, an optimal design for minimizing automotive wheel stress and increasing wheel safety is described. To study the optimal design, a central composite design (CCD) and D-optimal design theory are applied, and the approximate function using the response surface method (RSM) is generated. The optimal solutions using the non-dominant sorting genetic algorithm (NSGA-II) are then derived. Comparing CCD and D-optimal solution accuracy and verified the CCD can deduce more accuracy optimal solutions.

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.

Optimal and Approximate Solutions of Object Functions for Base Station Location Problem (기지국 위치 문제를 위한 목적함수의 최적해 및 근사해)

  • Sohn, Surg-Won
    • The KIPS Transactions:PartC
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    • v.14C no.2
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    • pp.179-184
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    • 2007
  • The problem of selecting base station location in the design of mobile communication system has been basically regarded as a problem of assigning maximum users in the cell to the minimum base stations while maintaining minimum SIR. and it is NP hard. The objective function of warehouse location problem, which has been used by many researchers, is not proper function in the base station location problem in CDMA mobile communication, The optimal and approximate solutions have been presented by using proposed object function and algorithms of exact solution, and the simulation results have been assessed and analyzed. The optimal and approximate solutions are found by using mixed integer programming instead of meta-heuristic search methods.

BPN Based Approximate Optimization for Constraint Feasibility (구속조건의 가용성을 보장하는 신경망기반 근사최적설계)

  • Lee, Jong-Soo;Jeong, Hee-Seok;Kwak, No-Sung
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2007.04a
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    • pp.141-144
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    • 2007
  • Given a number of training data, a traditional BPN is normally trained by minimizing the absolute difference between target outputs and approximate outputs. When BPN is used as a meta-model for inequality constraint function, approximate optimal solutions are sometimes actually infeasible in a case where they are active at the constraint boundary. The paper describes the development of the efficient BPN based meta-model that enhances the constraint feasibility of approximate optimal solution. The modified BPN based meta-model is obtained by including the decision condition between lower/upper bounds of a constraint and an approximate value. The proposed approach is verified through a simple mathematical function and a ten-bar planar truss problem.

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Economic production quantity with expontial deterioration

  • Hwang, Hark;Kim, Kap-Hwan
    • Journal of the Korean Operations Research and Management Science Society
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    • v.4 no.1
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    • pp.53-58
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    • 1979
  • Production lot sizing problem for a system with exponentially decaying inventory is considered. From the exact cost function developed under conditions of constant demand and no shortages permitted, an approximate optimal solution is derived. The formula is compared with those of the exact solution obtained from numerical procedure and other existing approximate solution. Finally some notable properties of the formula are investigated and shown to be consistent.

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