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Complex high-dimension system optimization method based on quick mode pursuing sampling

A system optimization and complex technology, applied in the field of complex high-dimensional system optimization, can solve problems such as slow convergence speed and missing global optimal solution, and achieve the effects of improving reliability, shortening the optimization design cycle, and reducing computing costs

Active Publication Date: 2018-08-28
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0017] The purpose of the present invention is to solve the problem that the existing space-reducing sequence sampling method and the space-filling sequence sampling method are difficult to achieve a good balance between the local search ability and the global exploration ability, and then the global optimal solution is easily missed, or the convergence speed Slow problem, providing a complex high-dimensional system optimization method based on fast peak-chasing sampling

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  • Complex high-dimension system optimization method based on quick mode pursuing sampling
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  • Complex high-dimension system optimization method based on quick mode pursuing sampling

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Embodiment Construction

[0041] In order to further illustrate the purpose and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, and through two typical global optimizations with the standard peak pursuit sampling method (MPS) and genetic algorithm (Genetic Algorithm, GA) The results of the algorithms are compared, and the comprehensive performance of the present invention is verified and analyzed.

[0042] The specific implementation process will be described below through an example of wing weight optimization design as an example. The empirical solution formula for wing weight is as follows:

[0043]

[0044] where x 1 ,...,x 10 The corresponding physical meanings and value ranges are shown in Table 1.

[0045] Table 110 dimensional wing weight optimization problem parameter list

[0046]

[0047] The reference values ​​in Table 1 come from the classic Cessna C172 "Skyhawk" sma...

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Abstract

The invention relates to a complex high-dimension system optimization method based on quick mode pursuing sampling, and belongs to the technical field of engineering optimization design. The method comprises the following steps that: firstly, in a design space, constructing the agent model of an engineering system complex analysis model; then, dividing sequence sample points iterated each time into global search sample points and local search sample points; and according to the approximation accuracy and approximation optimal solution convergence situation of the agent model, continuously updating a major design space until the optimal solution of an optimal design problem is obtained. By use of the method which is put forward by the invention, the defects of a standard mode pursuing sampling method that time is consumed for calculation when the complex high-dimension system is optimized are overcome, optimization efficiency is improved, calculation cost is lowered, and therefore, themethod is favorable for shortening an optimization design period.

Description

technical field [0001] The invention relates to a complex high-dimensional system optimization method based on fast peak-chasing sampling, and belongs to the technical field of engineering optimization design. Background technique [0002] Applying optimization design techniques to engineering design problems can improve design results and shorten design cycles. In order to improve design credibility, it is necessary to calculate high-precision models, such as structural finite element analysis (Finite Element Analysis, FEA), computational fluid dynamics (Computational Fluid Dynamics, CFD), stealth computational electromagnetics (Computational Electromagnetics, CEM), etc., these Model calculations are extremely time-consuming. Traditional gradient-based local search algorithms (such as augmented Lagrange multiplier method, sequential quadratic programming, feasible direction method) and probability-based global exploration algorithms (such as genetic algorithm, simulated an...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/15
CPCG06F17/15
Inventor 刘莉武宇飞龙腾史人赫
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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