多目标野山羊算法的动压滑动轴承优化设计  

Optimum Design of Hydrodynamic Sliding Bearing Based on Multi-Objective Wild Goat Algorithm

作　　者：高淑芝 仰雷雨 张义民[1] GAO Shu-zhi;YANG Lei-yu;ZHANG Yi-min(Institute of Equipment Reliability,Shenyang Chemical University,Liaoning Shenyang 110142,China;College of Information Engineering,Shenyang Chemical University,Liaoning Shenyang 110142,China)

机构地区：[1]沈阳化工大学装备可靠性研究所,辽宁沈阳110142 [2]沈阳化工大学信息工程学院,辽宁沈阳110142

出　　处：《机械设计与制造》2023年第5期206-210,共5页Machinery Design & Manufacture

基　　金：NSFC-国家自然科学重点基金-辽宁联合基金(U1708254);辽宁省特聘教授(No.[2018]3533)项目。

摘　　要：野山羊算法结合不同的搜索策略,弥补了多个著名元启发式算法在解决优化问题中的固有缺陷。针对传统野山羊算法不能有效解决多目标优化问题,提出了多目标野山羊算法并应用于多目标优化当中。首先该算法在野山羊算法基础上提出了改进的多种群策略,提升了种群多样性;其次将该策略与提出的动态进化策略和领头羊派遣策略结合,进一步增强了个体之间的信息交流,防止算法局部收敛。再者将该算法与其他经典多目标优化算法比较,实验结果表明提出的算法在解决多目标优化问题中具有明显优势。最后将该算法应用到动压滑动轴承的多目标优化设计当中。The Wild Goat algorithm combines different search strategies to make up for the inherent drawbacks of several wellknown metaheuristic algorithms in solving optimization problems.For the traditional wild goat algorithm can not solve the multiobjective optimization problem effectively,a multi-objective wild goat algorithm is proposed and applied to the multi-objective optimization.Firstly,the algorithm proposed an improved multiple population strategy based on the wild goat algorithm,which improved the population diversity.Secondly,it combined the strategy with the proposed dynamic evolution strategy and the dispatch strategy of the leader goats to further enhance the information exchange between individuals and prevent the algorithm from local convergence.Moreover,the algorithm is compared with other classical multi-objective optimization algorithms.The experimental results show that the proposed algorithm has obvious advantages in solving multi-objective optimization problems.Finally,the algorithm is applied to the multi-objective optimal design of hydrodynamic sliding bearings.

关 键 词：多目标优化 动压滑动轴承 元启发式算法 野山羊算法 

分 类 号：TH16[机械工程—机械制造及自动化] TP18[自动化与计算机技术—控制理论与控制工程]