陆凤仪;于浩洋;徐格宁;

• 1:太原科技大学机械工程学院

摘要(Abstract)：

针对粒子群算法在解决高维度复杂优化易陷入局部最优的问题,构建差分进化算法(DE)、人工蜂群算法(ABC)与粒子群算法(PSO)并行运算的种群更新模型,提出基于并行策略的改进混合粒子群算法(DA_PSO)。以并行策略为基础,不改变种群规模,独立运行3种算法,每隔n次比较3种算法,获得当前最优点,并用其替换粒子群算法的种群最优点,利用PSO算法个体向种群最优靠近的特点,充分吸收DE算法、ABC算法的优点,使被替换后的PSO算法跳出局部最优,提升优化结果的质量。采用五种类型测试函数分别对ABC、DE、PSO和DA_PSO进行对比验证,结果表明:较其他算法而言,DA_PSO算法精度高,稳定性好,适应性强。同时为验证所提方法的科学性与实用性,将其应用在10t～32t/31.5m系列化的桥式起重机主梁金属结构轻量化设计中。

关键词(KeyWords)： 并行策略;DA＿PSO算法;人工蜂群算法;差分进化算法;主梁金属结构

Abstract:

Keywords:

基金项目(Foundation): 十三五"国家重点研发计划—港口等领域典型起重机械设计制造与服役过程风险防控关键技术研究（2017YFC0805703）

作者(Author): 陆凤仪;于浩洋;徐格宁;

Email:

DOI: 10.19356/j.cnki.1001-3997.2021.03.050

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