Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism

Ye Bin; Luo Jinliang

doi:10.16578/j.issn.1004.2539.2017.07.037

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Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism

更新时间：2022-10-20

- Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism
- Vol. 41, Issue 7, Pages: 176-179(2017)
- 作者机构：
  
  1. 南华大学机械工程学院
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2017.07.037
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[1]叶彬,罗金良.改进FGA算法及其在四杆机构优化设计中的应用[J].机械传动,2017,41(07):176-179.

Ye Bin, Luo Jinliang. Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism. [J]. 41(7):176-179(2017)
[1]叶彬,罗金良.改进FGA算法及其在四杆机构优化设计中的应用[J].机械传动,2017,41(07):176-179. DOI： 10.16578/j.issn.1004.2539.2017.07.037.

Ye Bin, Luo Jinliang. Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism. [J]. 41(7):176-179(2017) DOI： 10.16578/j.issn.1004.2539.2017.07.037.

摘要

遗传算法可以有效地处理一些常规优化方法不能解决的复杂优化问题。然而,传统遗传算法存在容易陷入局部解、收敛速度慢和处理带约束优化问题效果不佳等缺点。提出了一种采用浮点数编码方法处理不等式约束优化问题的改进遗传算法（Float-encoding Genetic Algorithm,FGA）,该算法具有收敛效率高、算法稳定性好和局部搜索能力强等优点。运用该算法对曲柄连杆机构进行优化设计,优化结果表明,改进后的遗传算法比传统遗传算法优化效果更好。

Abstract

The genetic algorithm can effectively handle some complex optimal problems that the conventional optimization methods can’t solve. However,the traditional genetic algorithm has many defects,such as falling easily into local solution,slower convergence speed and the poor effect of optimal problems with constraints. An improved float-encoding genetic algorithm（ FGA） solving optimal problems with inequality constraints is proposed. This method has the advantages of high convergence efficiency,good stability and strong local search capability. It is used to the optimal design of crank-link mechanism,and the optimal results show that the improved genetic algorithm has a better effect than the traditional genetic algorithm.

关键词

改进FGA算法曲柄连杆机构不等式约束优化设计

Keywords

Improved FGA algorithmCrank-link mechanismInequality constraintOptimal design

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