Results 161 to 170 of about 163,780 (214)

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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Optimization design of rockoons based on improved sequential approximation optimization

Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2021
In this study, a multidisciplinary design optimization framework and detailed procedure based on improved sequential approximation optimization (SAO) and 3-degree-of-freedom trajectory simulation are proposed for conceptual design and parameters optimization of a rockoon (from rocket and balloon) system.
Jiaxin Li, Ke Peng, Wenjie Wang, Zeping Wu, Weihua Zhang   +4 more
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Parallel Processing in Sequential Approximate Optimization

43rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2002
The paper presents a first level of coarse-grained parallelization in a sequential approximate optimization framework. A sequential approximate optimization framework builds local approximations of the system every iteration by evaluating a set of design points around the current design.
Victor Perez, Thomas Apker, John Renaud
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An Object-Oriented Framework for Sequential Approximate Optimization

9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 2002
A sequential approximate optimization method is used to optimize computational expensive or non-smooth output behavior of simulation models. In this paper a flexible and compact object-oriented framework is proposed that supports the implementation and use of a sequential approximate optimization strategy.
Jacobs, J.H., Etman, L.F.P., Keulen, van, A., Rooda, J.E.   +3 more
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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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Approximately Optimal One-Parameter Boundaries for Group Sequential Trials

Biometrics, 1987
We present a class of group sequential tests, indexed by a single parameter, that yields approximately optimal results. We also provide tables of key values to help in the design of group sequential tests that meet selected specifications.
Wang, Samuel K., Tsiatis, Anastasios A.
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Sequential Approximate Optimization

2009
In many practical engineering design problems, the form of objective functions is not given explicitly in terms of design variables. Given the value of design variables, under this circumstance, the value of objective functions is obtained by some analysis such as structural analysis, fluid mechanic analysis, and thermodynamic analysis.
Hirotaka Nakayama, Yeboon Yun, Min Yoon
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Sequential approximation optimization assisted particle swarm optimization for expensive problems

Applied Soft Computing, 2019
Abstract In this paper, an efficient sequential approximation optimization assisted particle swarm optimization algorithm is proposed for optimization of expensive problems. This algorithm makes a good balance between the search ability of particle swarm optimization and sequential approximation optimization. Specifically, the proposed algorithm uses
Xiwen Cai, Liang Gao, Fan Li
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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 in an NLP Filter Framework

11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2006
Nonlinear programming (NLP) filter methods are a recent development in trust region sequential quadratic programming (SQP) algorithms. The NLP filter is a bi-objective representation of the two competing aims to minimize the objective function and to satisfy the constraints.
L. F. Pascal Etman, A. Groenwold, J. Rooda   +2 more
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