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Approximate optimization method based on particle swarm optimization and Kriging model

A particle swarm optimization and optimization method technology, applied in design optimization/simulation, special data processing applications, instruments, etc., to avoid missing global optimal solutions, improve global and local search capabilities, and improve reliability.

Inactive Publication Date: 2018-12-21
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

The present invention is suitable for application in the field of design and optimization of complex engineering systems including high-precision analysis models, and can solve corresponding related engineering problems

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  • Approximate optimization method based on particle swarm optimization and Kriging model
  • Approximate optimization method based on particle swarm optimization and Kriging model
  • Approximate optimization method based on particle swarm optimization and Kriging model

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Embodiment 1

[0077] The specific implementation process will be described below through a design example of a pressure vessel as an example.

[0078] The purpose of the Pressure Vessel Design (PVD) problem is to reduce design costs including welding, materials, and forming. The pressure vessel needs to store 750ft at 3000psi 3 air, shaped like figure 1 shown. The PVD problem contains four design variables, x 1 is the thickness of the spherical head, x 2 is the shell thickness, x 3 is the radius, x 4 is the length. The optimized model expression is as follows:

[0079]

[0080] In this embodiment, the design variable n is taken v =4. The approximate optimization method based on particle swarm optimization and Kriging model disclosed in this embodiment, the specific implementation steps are as follows:

[0081] Step 1: In the initial design space, initial sample points are generated through the Latin hypersquare experimental design, and the number of iterations k=1. According t...

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Abstract

The invention discloses an approximate optimization method based on particle swarm optimization and Kriging model, which belongs to the technical field of engineering optimization design. A method forrealize that invention comprises the follow steps of: using particle swarm evolution to guide simple sample points to aggregate to a global optimal solution; adopting fuzzy c- Mean clustering methodis used to cluster simple sample points to identify the region of interest, so as to fully mine the design space information on the basis of balancing local search and global exploration. By adding high-precision sample points in the region of interest sequence and updating the Kriging model constantly, the optimization converges to the global optimal solution quickly. The invention can effectively improve the global exploring ability and the local searching ability of the optimization method, reduce the calculation cost in the optimization process of the complex engineering system, avoid missing the global optimal solution as far as possible, and improve the reliability of the design result. The invention is suitable for application in the field of complex engineering system design optimization including a high-precision analysis model, and can solve corresponding related engineering problems.

Description

technical field [0001] The invention relates to an approximate optimization method based on particle swarm optimization and Kriging model, and belongs to the technical field of engineering optimization design. Background technique [0002] In order to improve design quality and reduce repeated design, Multidisciplinary Design Optimization (MDO) has been widely used in the design of complex engineering systems. However, in the design process of complex engineering systems, it is necessary to call high-precision simulation analysis models (such as finite element models) to improve design reliability, resulting in a sharp increase in optimization costs. In addition, MDO problems usually need to be solved iteratively through a multidisciplinary analysis (Multidisciplinary Analysis, MDA) process, which further aggravates the computational complexity. In order to alleviate the computational complexity faced by spacecraft MDO, Metamodel-based Design and Optimization (MBDO) has att...

Claims

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/23
Inventor 王东刘莉龙腾武宇飞
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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