基于Pareto解集蚁群算法的拆卸序列规划

为提高产品拆卸序列规划的效率,分析拆卸序列规划问题中的多个优化目标平衡问题,提出一种基于Pareto解集的多目标蚁群优化算法求解此类拆卸规划问题,并给出拆卸序列的构建过程。通过利用拆卸矩阵推导拆卸可行条件,获得可以执行拆卸操作的零件及其可行的拆卸方向。通过利用零件的轴向包围盒(Axis aligned bounding boxes,AABB)计算零件的拆卸行程。考虑拆卸方向改变次数、拆卸总行程、拆卸零件数量为优化目标,通过利用蚁群算法搜索可行解并计算各个解之间的支配关系,得到Pareto解集,实现求解优化的拆卸序列,给出算法的具体步骤。最后以单杠发动机为拆卸实例,利用所提方法进行拆卸序列规划求解,通过分析试验结果,并对比典型的单目标蚁群规划算法,证明了该方法的高效性和可行性。

Disassembly Sequence Planning Based on Pareto Ant Colony Algorithm

To improve product disassembly planning efficiency,the multi-objective disassembly planning problem is analyzed,therefore,a multi-objective ant colony algorithm based on Pareto set is proposed,and the construction process of disassembly sequences is presented.To acquire the feasibility disassembly parts and disassembly directions the disassembly matrix is used to derivate the feasible condition of disassembly.The axis aligned bounding boxes is utilized for calculating the disassembly distance of part.The optimal sequence concerning with minimizing the changes of disassembly direction,total disassembly distance and the sequence length is given.The ant colony algorithm is utilized for searching the solutions and the Pareto solution set is acquired by calculating the dominance relations between solutions.The specific steps of algorithm are given.Finally,compared with a typical single target ant colony planning algorithm an internal combustion engine case is conducted to demonstrate the feasibly and efficiency of the proposed method.