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Device failure is the most common dynamic event in shop floor scheduling, which easily affects the original production scheduling plan. In order to ensure that processing production can quickly make adjustments to the original scheduling plan after encountering device failure and reduce the negative impact caused by device failure, the scheduling problem of no-idle multi-device work center under device failure is studied. Firstly, a no-idle hybrid flow shop scheduling model considering setup time and handling time under device failure is established, and the optimization objectives are completion time, handling times and system stability. Secondly, the NSGA-II-V algorithm is designed for solving the original scheduling and rescheduling. Finally, based on the static scheduling results obtained by NSGA-II-V with the idea of partial rescheduling strategy, the device failure cases are tested, and the test results show that the proposed model and algorithm can better handle the zero-idle hybrid flow shop scheduling problem where the dynamic event is completion time failure. [ABSTRACT FROM AUTHOR]

The order processing of robotic mobile fulfillment systems is studied according to the difference between robotic mobile fulfillment systems and the traditional warehouse. A heuristic algorithm for shared storage optimization is proposed as the basis for research. To obtain satisfactory order sequencing and rack scheduling of dynamic picking, a hybrid algorithm is proposed, where considers the order similarity, cyclic greedy crossover, and bounce mechanism. Experimental results show that compared with other decision-making methods, the algorithm can reduce the number of times of shelf scheduling by up to 47% in small-scale problems and effectively improve the fulfillment efficiency of orders. [ABSTRACT FROM AUTHOR]