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Parallel computing global optimization algorithm based on Kriging agent model

A surrogate model and global optimization technology, applied in complex mathematical operations and other directions, can solve the problems of low optimization efficiency and unsatisfactory accuracy of single-point addition criteria, and achieve the effect of easy understanding and programming

Active Publication Date: 2019-12-24
DALIAN UNIV OF TECH
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Problems solved by technology

[0003] Aiming at problems such as low optimization efficiency and unsatisfactory precision of the single-point adding criterion based on the agent model, the present invention provides a kind of high-efficiency and high-precision optimization algorithm (PEI-R algorithm) suitable for parallel computing

Method used

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  • Parallel computing global optimization algorithm based on Kriging agent model
  • Parallel computing global optimization algorithm based on Kriging agent model
  • Parallel computing global optimization algorithm based on Kriging agent model

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Embodiment Construction

[0040] In order to make the flow and function of the optimization algorithm clearer, the specific embodiments of the present invention will be described in detail below in conjunction with the technical solutions and accompanying drawings.

[0041] Here, the principal stress distribution of the film is controlled by optimizing the shape of the fixture, taking the elimination of stretched film wrinkles as an example to illustrate the optimization algorithm process and function, but the function of the algorithm is not limited to this. The schematic diagram of the fixture and film structure is shown in figure 1 . The shape optimization problem is formulated as follows

[0042] find x=[x 1 ,x 2 ,...,x 6 ] T

[0043]

[0044] s.t.R(u)=0

[0045] 0≤x i ≤1(i=1,2,...,6)

[0046] where x=[x 1 ,x 2 ,...,x 6 ] T The abscissa controls the fixture shape for the six design points, S * =0.012Mpa is the fixed value, is the minimum principal stress of each finite element el...

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Abstract

The invention discloses a parallel computing global optimization algorithm based on a Kriging agent model, namely a PEI-R algorithm, and belongs to the technical field of global optimization algorithms. According to the method, the agent model method is matched with the parallel point adding criterion, so that the efficient and high-precision global optimization calculation is achieved. A main sample and a local sampling strategy are selected through a P-EI criterion to increase the calculation efficiency of the algorithm so as to design a domain reduction strategy to improve the precision ofthe algorithm. According to the method, the efficient parallel computing can be achieved through the multi-core parallel capacity of a computer, the efficiency can be improved by three times comparedwith a traditional EI sequence point adding criterion, and the precision is improved by at least one order of magnitude. The method is good in universality and few in calculation times of the target function, not only is suitable for a conventional optimization problem, but also is suitable for solving the complex engineering and multidisciplinary optimization problems which cannot obtain gradients.

Description

technical field [0001] The invention belongs to the technical field of global optimization algorithms, and relates to a parallel computing optimization algorithm (PEI-R algorithm) based on a proxy model and a sequence adding point criterion. Background technique [0002] At present, the mainstream methods for global optimization include: gradient-based multi-initial point search method, intelligent algorithm and agent model optimization algorithm. Among them, the proxy model algorithm has the advantages of not requiring gradient information, less calculation times of the objective function, and having the ability of global optimization, etc., and is widely used. The proxy model algorithm usually has two methods of direct optimization based on the model and optimization by adding points. The latter has low requirements on initial model accuracy and high optimization accuracy, and is the main solution to engineering optimization problems. However, the single-point addition c...

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Application Information

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IPC IPC(8): G06F17/15
CPCG06F17/15
Inventor 罗阳军邢健
Owner DALIAN UNIV OF TECH
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