东北大学学报（自然科学版）

东北大学学报（自然科学版） ›› 2023, Vol. 44 ›› Issue (2): 223-232.DOI: 10.12068/j.issn.1005-3026.2023.02.010

• 机械工程 • 上一篇    下一篇

基于改进樽海鞘群算法的提梁机主梁轻量化设计方法

陈一馨1,2， 张婷1， 刘永刚2， 陈晶1   

  1. (1. 长安大学 道路施工技术与装备教育部重点实验室， 陕西 西安710064； 2. 河南卫华重型机械有限公司， 河南 长垣453400)
  • 修回日期:2021-12-11 接受日期:2021-12-11 发布日期:2023-02-27
  • 通讯作者: 陈一馨
  • 作者简介:陈一馨(1984-)，女，甘肃天水人，长安大学副教授，研究生导师.
  • 基金资助:
    陕西省自然科学基金资助项目(2019JQ-556，2022JQ-576， 2022JM-295)； 河南省博士后科研项目启动资助； 陕西省国际科技合作项目(2019KW-015).

Lightweight Design Method of Girder Hoist Based on Improved Salp Swarm Algorithm

CHEN Yi-xin1,2， ZHANG Ting1， LIU Yong-gang2， CHEN Jing1   

  1. 1. Key Laboratory of Road Construction Technology & Equipment， Ministry of Education， Chang’an University， Xi’an 710064， China. 2. Henan Weihua Heavy Machinery Co.，Ltd.， Changyuan 453400， China.
  • Revised:2021-12-11 Accepted:2021-12-11 Published:2023-02-27
  • Contact: CHEN Yi-xin
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摘要： 针对樽海鞘群算法在优化过程中存在收敛速度慢、求解精度低、易于陷入局部最优解等缺点，提出了基于柯西和高斯混合变异的一种自适应变异策略的樽海鞘群算法，该算法通过选出适应度值最好的前S个个体进行自适应变异，可避免算法陷入局部最优解.通过柯西和高斯变异动态调整参数的变化提高算法的局部搜索能力和收敛速度.选取10个测试函数分别对樽海鞘群算法及改进樽海鞘群算法进行测试比较.数值分析表明，改进的樽海鞘群算法收敛速度快，寻优能力强且精度高.将改进后的算法用于提梁机主梁结构的优化设计中，该结构在满足强度、刚度、稳定性等设计要求条件下，主梁的截面积减少了13.58%，轻量化效果显著，表明该算法具有良好的工程应用价值.

关键词: 樽海鞘群算法；自适应变异策略；柯西变异；高斯变异；提梁机主梁；轻量化

Abstract: In view of the disadvantages of slow convergence， low solution accuracy and tendencies to fall into local optimal solutions in the optimization process， an improved adaptive mutation strategy of salp swarm algorithm based on Cauchy and Gaussian mixture mutation was proposed. The algorithm tend not to fall into local optimal solution by selecting the first S individuals with the best fitness value for adaptive variations， and the local search capability and convergence speed of the algorithm is improved by dynamically adjusting the size variation of the parameters through the Cauchy and Gaussian variants. Ten test functions were selected to test and compare the salp swarm algorithm and the improved adaptive mutation salp swarm algorithm respectively. Numerical analysis showed that the improved salp swarm algorithm has fast convergence speed， strong search ability and high accuracy. The improved algorithm was applied to the optimization design of the main beam structure of the beam lifter. Under the condition of meeting the design requirements of strength， stiffness and stability， etc.， the cross-sectional area of the main beam is reduced by 13.58 %， and the weight reduction effect is significant， indicating that the algorithm has good engineering application value.

Key words: salp swarm algorithm; adaptive mutation strategy; Cauchy mutation; Gaussian mutation; girder hoist; weight reduction

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