Abstract: To improve the efficiency and profit of product remanufacturing disassembly,a multi-objective selective disassembly sequence planning method based on improved multi-objective frog-leaping algorithm was proposed.The disassembly information modeling method was optimized,and the fastener constraint matrix and part constraint matrix were used to construct a product disassembly information model and a feasible solution.With the goal of minimizing disassembly time and maximizing disassembly benefits,a new multi-objective selective sequence evaluation method was proposed and a mathematical model for selective disassembly sequence planning of multi-target pieces was constructed.A multi-objective improved frog jumping algorithm was established by integrating Pareto's idea,and a three-stage coding was proposed to construct frog individuals,which achieved the diversity adjustment of selective disassembly sequences.An improved sort grouping strategy based on the idea of fast non-dominated sorting and congestion comparison was used to group multi-objective optimized frogs.An adjustment order method based on the adjustment position was proposed to discretize the local search method of the sub-frog group,and a new formula for updating the individual frog position was built.An adjustment order method based on the adjustment position was proposed to discretize the local search method of the sub-frog group,and a new formula was constructed for updating the individual frog position.To take into account the depth and diversity of information interaction,a new crossover and mutation idea was proposed to construct a global information interaction strategy.The improved multi-target frog jumping algorithm was compared with the multi-objective algorithm NSGA-II and particle swarm optimization algorithm through multi-scale disassembly examples.Experimental results verified the algorithm feasibility and superiority.

Key words: disassembly modeling, selective disassembly sequence planning, multi-objective components, multi-objective shuffled frog leaping algorithm, disassembly solution

摘要： 为提高产品再制造拆卸效率与收益,提出基于多目标改进蛙跳算法的多目标件选择性拆卸序列规划方法。首先优化拆卸信息建模方法,利用紧固件约束矩阵和结构件约束矩阵,构建产品拆卸信息模型并构造可行解;以拆卸时间最小化和拆卸收益最大化为目标,以多目标件价值为导向构建一种新的多目标选择性序列评价方法,同时构建多目标件选择性拆卸序列规划数学模型。融入Pareto思想构建多目标改进蛙跳算法,提出三段式编码构建青蛙个体,以实现选择性拆卸序列的多样性调节;采用基于快速非支配排序与拥挤度比较思想的改进排序分组策略进行多目标优化蛙群分组;提出基于调节位置的调节序方法对子蛙群局部搜索方式进行离散化处理,并构建新的青蛙个体位置更新公式,同时通过构建青蛙个体更新次劣域增加信息源以实现子群体充分交流;为兼顾信息交互深度和多样,提出一种新的交叉和变异思想构建全局信息交互策略。最后,通过不同规模的拆卸实例,将改进后的多目标蛙跳算法与多目标算法NSGA-Ⅱ和粒子群算法进行多指标对比分析,验证了该算法的可行性与优越性。

关键词: 拆卸建模, 选择性拆卸序列规划, 多目标件, 多目标蛙跳算法, 拆卸求解