摘要
针对微粒群算法易于陷入局部最优解、早熟的缺点,将Lévy飞行引入微粒速度迭代公式中,并动态改变微粒群速度迭代公式中Lévy飞行的权重值,提出动态Lévy飞行微粒群算法。根据T-S故障树理论,建立液压支架液压系统的可靠性模型,进而得出可靠性费用目标函数。将提出的动态Lévy飞行微粒群算法应用于液压支架液压系统的可靠性优化中,并通过标准微粒群算法、布谷鸟搜索算法和基于Lévy飞行微粒群算法比较,验证所提出算法的优越性。
Aimed at particle swarm optimization (PSO) algorithm' s drawbacks of trapping into local minima easily and premature convergence, this study puts forward a particle swarm iteration algorithm of Lévy flight, which will in-trodnce the theory of the Lévy flight and dynamic weight into particle velocity iteration and can be called dynamic Lévy flight particle swarm optimization, in which the weight value of Lévy flight is dynamically changed. According to the principle of T-S fault tree, the reliability model of the hydraulic system is established, and then the reliability cost objective function is obtained. The proposed algorithm is applied to the reliability optimization of the hydraulic system for the hydraulic support, and through comparison between standard particle swarm optimization, cuckoo search algo-rithm and Lévy flight particle swarm optimization, the superiority of the proposed algorithm has been verified.
出处
《液压与气动》
北大核心
2017年第3期17-21,共5页
Chinese Hydraulics & Pneumatics
基金
国家自然科学基金(51405426
51675460)
河北省自然科学基金(E2016203306)
关键词
液压系统
可靠性优化
微粒群算法
Lévy飞行
动态权重
hydraulic system, reliability optimization, particle swarm optimization, Lévy flight, dynamic weight