基于物理规划的履带起重机变幅系统多目标优化

Multi-objective optimization for luffing system of crawler crane based on physical programming

中文关键词: 履带起重机  变幅系统  物理规划  多目标混沌遗传算法

英文关键词: crawler crane  luffing system  physical programming  multi-objective chaotic genetic algorithm

中文摘要:

      履带起重机变幅系统具备足够的承载能力实现臂架俯仰,是整机的重要组成部分．通过分析变幅系统构件受力特点,建立了变幅系统力学和多目标优化模型．采用物理规划方法,基于构件极限荷载定义偏好函数,建立了综合优化评价函数．设计多目标混沌遗传算法求解问题,根据Pareto支配概念和精英策略保留较优解,并采用混沌局部搜索避免了过早收敛．算例分析表明,提出的方法可以优化构件间的几何关系且减小构件受力,对履带起重机总体参数设计具有指导意义．

英文摘要:

      he luffing system of crawler crane, an important part of whole crane, has enough capacity to realize the boom luffing. Analyzing the characteristics of components, the mechanical model of luffing system and the multi\|objective optimization model are built. Using the method of physical programming, an integrated optimization evaluation function is defined with preference functions based on limit loads of components. A multi\|objective chaotic genetic algorithm, updating solution set with Pareto domination and elitist strategy to retain the optimum solution set, and the chaotic local search to avoid premature convergence, is designed. Numerical example shows that the method can efficiently optimize geometrical relations of components to reduce forces and significantly guide the overall parameter design of crawler crane.