Abstract: For solving the distributed heterogeneous flexible flowline scheduling problem with multiple dedicated transportation resources,an integer programming model was constructed with the optimization objective of simultaneously minimizing the makespan and total energy consumption,and a Multi-Objective Differential Memetic Algorithm（MODMA）was proposed.A factory-job based vector coding was designed to describe the factory allocation and job processing sequence,and then a dynamic decoding based on machine-AGV linkage was used to complete the allocation of machines and AGVs to construct the feasible solution.High-quality initial memetic groups were generated by designing the co-initialization mechanism,and the global evolution of the memetic groups was achieved by differential mutation based on double-difference strategy,random positional crossover and multi-objective normalized simulated annealing.Futher a variable neighborhood search process based on the two-layer external file was proposed  combined with the elite strategy to make it locally optimal.Compared with some existing multi-objective evolutionary algorithms through simulation experiments,the results showed that the convergence and diversity of the non-dominated solution sets obtained by the proposed algorithm were better than those of the other comparative algorithms,and then the superiority of the proposed algorithm was verified.

Key words: distributed heterogeneous flexible flowline, multiple transport system, multi-objective differential memetic algorithm, energy consumption

摘要： 为求解考虑多专用运输资源的分布式异构柔性流水线调度问题,以同时最小化最大完工时间和总能耗为优化目标构建整数规划模型,并提出一种多目标差分模因算法。设计基于工厂工件的向量编码以描述工厂分配和工件加工顺序,进而采用基于机器-自动导引车（AGV）联动的动态解码完成机器与AGV的分配以构建可行解;通过设计协同初始化机制以生成高质量的初始模因组,然后经过基于双差分策略的差分变异,随机位置交叉,多目标归一化模拟退火实现模因组的全局进化;进而提出基于双层外部档案的变邻域搜索过程并结合精英策略使其得到局部优化。通过仿真实验与一些现有多目标进化算法进行对比,实验结果显示了所提算法所得非支配解集的收敛性与多样性均优于其他对比算法,进而验证了算法优越性。

关键词: 分布式异构柔性流水线, 多转运系统, 多目标差分模因算法, 能耗