针对复杂结构条件下的零部件装配路径自动求解困难的问题,提出基于障碍和贪心规则的快速扩展随机树(Rapidly-exploring random tree,RRT)算法。该算法以基本RRT算法为基础,采用随机采样、终点采样、局部采样相结合的采样方式,利用目标...针对复杂结构条件下的零部件装配路径自动求解困难的问题,提出基于障碍和贪心规则的快速扩展随机树(Rapidly-exploring random tree,RRT)算法。该算法以基本RRT算法为基础,采用随机采样、终点采样、局部采样相结合的采样方式,利用目标零件与障碍物的碰撞面片法向量和碰撞点位置来引导随机树的扩展方向,在每个扩展方向上按贪心规则进行扩展,并提出先平移后旋转的扩展策略。对求解得到的初始装配路径,提出运用分段线性拟合的方法进行路径自动优化。设计并开发了装配路径求解软件原型系统,进行了算例测试和实例应用,结果验证了算法的高效可行。展开更多
选择拆卸序列规划是产品维修或回收的重要环节,针对目前选择拆卸序列规划算法中自动化程度较低的问题,提出一种基于运动规划的选择拆卸序列规划方法。该方法首先根据复杂产品中零件数量繁多,形状不规则的特点,采用基于自适应动态多树的...选择拆卸序列规划是产品维修或回收的重要环节,针对目前选择拆卸序列规划算法中自动化程度较低的问题,提出一种基于运动规划的选择拆卸序列规划方法。该方法首先根据复杂产品中零件数量繁多,形状不规则的特点,采用基于自适应动态多树的快速扩展随机树(Rapidly-exploring random tree,RRT)算法对零件进行运动规划。在此基础之上,通过对装配体进行自动分层处理,分析零件间拆卸约束关系,构建装配体的拆卸约束关系图。最后通过对拆卸约束关系图的分析处理,获得目标零件的选择拆卸序列。以某底盘的目标零件为例,对提出的算法进行了验证。展开更多
The main objective of this paper is to propose a two-phase solution algorithm for solving the Inventory Routing Problem with Time Windows (IRPTW), which has not been excessively researched in the literature. The sol...The main objective of this paper is to propose a two-phase solution algorithm for solving the Inventory Routing Problem with Time Windows (IRPTW), which has not been excessively researched in the literature. The solution approach is based on (a) a simple simulation for the planning phase (Phase I) and (b) the Variable Neighborhood Search Algorithm (VNS) for the routing phase (Phase II). Testing instances are established to investigate algorithmic performance, and the computational results are then reported. The computational study underscores the importance of integrating the inventory and vehicle routing decisions. Graphical presentation formats are provided to convey meaningful insights into the problem.展开更多
文摘针对复杂结构条件下的零部件装配路径自动求解困难的问题,提出基于障碍和贪心规则的快速扩展随机树(Rapidly-exploring random tree,RRT)算法。该算法以基本RRT算法为基础,采用随机采样、终点采样、局部采样相结合的采样方式,利用目标零件与障碍物的碰撞面片法向量和碰撞点位置来引导随机树的扩展方向,在每个扩展方向上按贪心规则进行扩展,并提出先平移后旋转的扩展策略。对求解得到的初始装配路径,提出运用分段线性拟合的方法进行路径自动优化。设计并开发了装配路径求解软件原型系统,进行了算例测试和实例应用,结果验证了算法的高效可行。
文摘选择拆卸序列规划是产品维修或回收的重要环节,针对目前选择拆卸序列规划算法中自动化程度较低的问题,提出一种基于运动规划的选择拆卸序列规划方法。该方法首先根据复杂产品中零件数量繁多,形状不规则的特点,采用基于自适应动态多树的快速扩展随机树(Rapidly-exploring random tree,RRT)算法对零件进行运动规划。在此基础之上,通过对装配体进行自动分层处理,分析零件间拆卸约束关系,构建装配体的拆卸约束关系图。最后通过对拆卸约束关系图的分析处理,获得目标零件的选择拆卸序列。以某底盘的目标零件为例,对提出的算法进行了验证。
文摘The main objective of this paper is to propose a two-phase solution algorithm for solving the Inventory Routing Problem with Time Windows (IRPTW), which has not been excessively researched in the literature. The solution approach is based on (a) a simple simulation for the planning phase (Phase I) and (b) the Variable Neighborhood Search Algorithm (VNS) for the routing phase (Phase II). Testing instances are established to investigate algorithmic performance, and the computational results are then reported. The computational study underscores the importance of integrating the inventory and vehicle routing decisions. Graphical presentation formats are provided to convey meaningful insights into the problem.