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Pressure vessel structure optimization method based on improved Harris eagle optimization algorithm

A pressure vessel, optimization algorithm technology, applied in design optimization/simulation, instrumentation, calculation, etc., can solve problems such as robustness and poor search effect

Pending Publication Date: 2020-10-27
ZHENGZHOU UNIVERSITY OF LIGHT INDUSTRY
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Problems solved by technology

[0006] In view of the deficiencies in the above-mentioned background technology, the present invention proposes a pressure vessel structure optimization method based on the improved Harris Eagle optimization algorithm, which solves the problem of poor robustness and poor search effect of the Harris Eagle optimization algorithm in high-dimensional problems. technical problem

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  • Pressure vessel structure optimization method based on improved Harris eagle optimization algorithm
  • Pressure vessel structure optimization method based on improved Harris eagle optimization algorithm
  • Pressure vessel structure optimization method based on improved Harris eagle optimization algorithm

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Embodiment Construction

[0065] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0066] The HHO algorithm is inspired by the collaborative foraging behavior and attack strategy of Harris hawks. Its search process consists of two parts: the exploration phase and the development phase, such as figure 1 shown. During the exploration phase, the flock locates potential prey by means of surveillance and tracking. During the development phase, prey is hunted through four attack strategies.

[0067] 1. Exploration stage

[0068] D...

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Abstract

The invention provides a pressure vessel structure optimization method based on an improved Harris eagle optimization algorithm. The method comprises the following steps: firstly, determining all variables and change ranges affecting the structural performance of a pressure vessel through the mathematical modeling of the pressure vessel, and building a target function for the structural optimization of the pressure vessel; and then, optimizing the target function by utilizing an improved Harris eagle optimization algorithm to obtain an optimal value of each variable of the pressure vessel structure. According to the method, the adaptive cooperative foraging strategy is embedded into the one-dimensional position updating framework, and the one-dimensional updating operation and the traditional full-dimensional updating operation are adaptively selected according to the conversion factor, so that the population diversity of the algorithm is effectively improved; through a decentralized foraging strategy, part of Hamilk individuals are randomly decentralized to other areas for foraging, and the algorithm is prevented from falling into local optimum; according to the method, the consumption process of prey energy is better simulated by adopting a random exponential decay function, and the defect that the exploration stage and the development stage are unbalanced is overcome.

Description

technical field [0001] The invention relates to the technical field of pressure vessel structure optimization, in particular to a pressure vessel structure optimization method based on the improved Harris Eagle optimization algorithm. Background technique [0002] Optimization is the process of finding the best solution among all alternatives to a particular problem. Finding the optimal solution based on gradient information is difficult to adapt to the complex challenges of large-scale, multi-constraint, multi-modal, high-dimensional and other characteristics. In this context, the rapid development of swarm intelligence optimization algorithms is more efficient for solving such complex problems. [0003] The swarm intelligence algorithm is a typical natural heuristic algorithm, and its essence is a global probability search algorithm based on the behavior of biological groups. The swarm intelligence algorithm mainly relies on its simple concept, easy implementation, no ne...

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Application Information

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IPC IPC(8): G06F30/17G06F30/20G06N3/00
CPCG06F30/17G06F30/20G06N3/006
Inventor 张勋才刘玉雪李盼龙赵凯吴涛王延峰凌丹栗三一王妍王英聪孙军伟姜素霞黄春
Owner ZHENGZHOU UNIVERSITY OF LIGHT INDUSTRY
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