Abstract: For the lot streaming hybrid flowshop scheduling problem with missing operation,considering the adjustment time by batch changing,a integrated optimization model of flexible batch and scheduling was established by taking the minimize makepan and machine load balance as the optimization objectives,and a double-layer Particle Swarm optimization—Genetic Algorithm (PSO-GA) hybrid algorithm was proposed.The algorithm proposed the double-layer search solution frame for batch and machine,the outer layer carried out flexible batch and the inner layer searched the sorting and scheduling.Aiming at three problems:batch,lot sorting and machine assignment,the three-stage code based on batch,process and machine was designed.The inner layer introduced the grading and wandering strategy of the Grey Wolf Optimizer (GWO) into the PSO.A siege strategy based on Position based Crossover (PBX) cross operation was designed to improve the local search and optimization ability.Through simulation experiments、comparison with several heuristic algorithms and example verification,the feasibility and superiority of the scheduling model and algorithm were verified.

Key words: lot streaming, hybrid flowshop scheduling problem, missing operations, improved particle swarm optimization－genetic algorithm hybrid algorithm, double-layer search frame, flexible batch

摘要： 针对带忽略工序的批量流混合流水车间调度问题,在考虑批次切换调整时间的情况下,以最小化完工时间和机床负荷平衡为优化目标,建立柔性批量分割和调度集成优化模型,提出一种双层改进 PSO-GA混合算法。算法提出批量和机器的双层搜索求解框架,外层进行柔性分批,内层搜索排序及调度方案。针对批量分割、工件批排序、机器分配3个问题,设计基于批量、工序和机器的三段式编码,内层将狼群算法的分级和游走策略引入粒子群算法,设计了一种基于PBX(Position-based Crossover)交叉操作的围攻策略以提高算法的局部搜索及寻优能力。通过仿真实验并与几种启发式算法进行对比及实例验证,说明了调度模型和算法的可行性和优越性。

关键词: 批量流, 混合流水车间调度, 忽略工序, 改进PSO-GA混合算法, 双层搜索框架, 柔性分批