基于GWO-IWD算法的装配序列规划研究  

Research on Assembly Sequence Planning Based on GWO-IWD Algorithm

作　　者：刘鑫涛 叶树霞[1] 齐亮[1] LIU Xintao;YE Shuxia;QI Liang(School of Electronic Information,Jiangsu University of Science and Technology,Zhenjiang 212100)

机构地区：[1]江苏科技大学电子信息学院,镇江212100

出　　处：《计算机与数字工程》2024年第7期1927-1931,1980,共6页Computer & Digital Engineering

基　　金：国家自然科学基金项目(编号:51875270)资助。

摘　　要：针对复杂装配体装配序列规划问题,提出一种基于灰狼优化的智能水滴算法。综合考虑零件的属性特征及几何约束,构建装配体的装配信息模型,将装配成本作为优化的目标函数,以装配序列的几何可行性、装配方向改变次数以及装配工具改变次数为约束条件,建立面向装配体的优化模型。采用智能水滴算法对装配体优化模型进行求解,并利用灰狼优化算法来改善智能水滴算法的搜索能力,提高算法求解精度。以柱塞泵装配体单元为例,验证了该算法的可行性及有效性。Aiming at the assembly sequence planning problem of complex assembly,an intelligent water drop algorithm based on gray wolf optimization is proposed.Considering the attribute characteristics and geometric constraints of parts,the assembly infor⁃mation model of assembly is constructed,the number of times to optimize the assembly sequence and the number of times to change the assembly sequence are the objective constraints.The intelligent water drop algorithm is used to solve the assembly optimization model,and the gray wolf optimization algorithm is used to improve the search ability and accuracy of the intelligent water drop algo⁃rithm.Taking the assembly unit of piston pump as an example,the results verify the feasibility and effectiveness of the algorithm.

关 键 词：装配序列规划 干涉矩阵 智能水滴算法 灰狼优化 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]