基于混合离散蝙蝠算法的跨工序协同调度问题

Cross Process Coordinated Scheduling Problem Based on Hybrid Discrete Bat Algorithm

针对跨工序的生产与配送协同调度问题,构建了前工序单机批加工、后工序多产线逐订单加工,且工序之间采用自动引导车循环配送的协同调度模型。以最小化最大完工时间和后工序前的在制品等待时间为调度目标,设计了融合模拟退火算法与解串算法的混合离散蝙蝠算法,与改进的离散粒子群算法和Ullrich遗传算法相比,该算法能很好地减少后工序产线前的队列等待时间,缩短产品的生产周期。

Aiming at the problem of collaborative scheduling of production and distribution across processes,a collaborative scheduling model of single-machine batch processing in former process and order-by-order processing in latter process was constructed,and AGV circular distribution was adopted among the processes.A hybrid discrete bat algorithm,which is combined with simulated annealing algorithm and modified unstring and string algorithm,was designed to minimize the maximum completion time and waiting time before subsequent process.Compared with the improved discrete particle swarm optimization and Ullrich genetic algorithm,the proposed algorithm may reduce queue waiting time and production cycle of products.