Results 221 to 230 of about 18,713 (263)

Sequential Approximate Optimization Using Kriging Metamodels

Transactions of the Korean Society of Mechanical Engineers A, 2005
Nowadays, it is performed actively to optimize by using an approximate model. This is called the approximate optimization. In addition, the sequential approximate optimization (SAO) is the repetitive method to find an optimum by considering the convergence of an approximate optimum.
Yongshik Shin, Yongbin Lee, Je-Seon Ryu, Dong-Hoon Choi   +3 more
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Multipoint Cubic Surrogate Functions for Sequential Approximate Optimization

9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 2002
Multipoint cubic approximations are investigated as surrogate functions for nonlinear objective and constraint functions in the context of sequential approximate optimization. The proposed surrogate functions match actual function and gradient values, including the current expansion point, thus satisfying the zero and first-order necessary conditions ...
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Sequential approximate optimization using variable fidelity response surface approximations

Structural and Multidisciplinary Optimization, 2001
The dimensionality and complexity of typical multidisciplinary systems hinders the use of formal optimization techniques in application to this class of problems. The use of approximations to represent the system design metrics and constraints has become vital for achieving good performance in many multidisciplinary design optimization (MDO) algorithms.
RODRIGUEZ MATAS, JOSE FELIX, Pérez, V. M., Padmanabhan, D., Renaud, J. E.   +3 more
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Sequential greedy approximation for certain convex optimization problems

IEEE Transactions on Information Theory, 2003
Summary: A greedy algorithm for a class of convex optimization problems is presented. The algorithm is motivated from function approximation using a sparse combination of basis functions as well as some of its variants. We derive a bound on the rate of approximate minimization for this algorithm, and present examples of its application.
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On approximation of optimal stopping of bayesian sequential test for a normal mean

Applied Mathematics-A Journal of Chinese Universities, 1995
We present a simple and direct approach in which supermartingales are used to approximate the optimal stopping sets associated with the Bayesian sequential test for normal population means. Serveral conclusions are given. The sequential tests for normal population means often arise from or are created through approximations or transformations in ...
Wan, Fanghuan, Wu, Xizhi
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Improved Sequential Approximate Optimization for Aerodynamic Design Benchmark Problem

2019 IEEE Congress on Evolutionary Computation (CEC), 2019
A modified surrogate-based optimization method based on Sequential Approximate Optimization (SAO) is proposed to purposively improve the efficiency of aerodynamic shape optimization. In this method, a specific initial sampling approach is proposed to obtain the initial sampling set of excellent properties of space-filling and orthogonality in the shape
Wenjie Wang, Zeping Wu, Donghui Wang, Weihua Zhang   +3 more
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Saddlepoint Approximation for Sequential Optimization and Reliability Analysis

Journal of Mechanical Design, 2007
A good balance between accuracy and efficiency is essential for reliability-based design (RBD). For this reason, sequential-loops formulations combined with the first-order reliability method (FORM) are usually used. FORM requires a nonlinear non-normal-to-normal transformation, which may increase the nonlinearity of a probabilistic constraint function
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Sequential multipoint quadratic approximation for numerical optimization

19th AIAA Applied Aerodynamics Conference, 2001
A quadratic approximation for nonlinear functions in a design sub-space is developed in order to realize computational savings in solving numerical optimization problems. Function and gradient information accumulated from multiple design points during the iteration history is used in estimating the reduced Hessian matrix.
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Structural design employing a sequential approximation optimization approach

Computers & Structures, 2014
This paper presents an improved sequential approximation optimization (SAO) algorithm that is suitable for structural design optimization tasks. First, an adaptive sampling strategy is proposed to balance between the competence to locate the global optimum and the computation efficiency in the optimization process.
Donghui Wang, Zeping Wu, Yang Fei, Weihua Zhang   +3 more
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On the equivalence of optimality criterion and sequential approximate optimization methods in the classical topology layout problem

International Journal for Numerical Methods in Engineering, 2007
AbstractWe study the ‘classical’ topology optimization problem, in which minimum compliance is sought, subject to linear constraints. Using a dual statement, we propose two separable and strictly convex subproblems for use in sequential approximate optimization (SAO) algorithms.Respectively, the subproblems use reciprocal and exponential intermediate ...
Groenwold, A.A., Etman, L.F.P.
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