An effective reformative memetic algorithm for distributed flexible job-shop scheduling problem with order cancellation

Order cancellation, due to such as customer plan adjustments or market changes, usually occurs in the real production environment of distributed flexible job shop scheduling problem (DFJSP). However, thus far, all exiting researches about DFJSP have not consider order cancellation, which normally leads to resource waste and makes the original scheme infeasible. Hence, in this work, we propose a DFJSP considering order cancellation (DFJSPC) for the first time; and design a reformative memetic algorithm (RMA) to solve the DFJSPC aiming at optimizing the makespan and total energy consumption. In the RMA, a five-layer encoding operator and a new load balancing initialization method are designed to improve the quality of the initial population. Some effective crossover, mutation and local search operators are designed, which can fully expand the solution space of the algorithm and improve its convergence speed. A total of 60 DFJSPC benchmark instances are constructed, and some comparative experiments are carried out among the proposed RMA and three well-known algorithms, namely NNIA, NSGA-II and NSGA-III. The final experimental results verified the outstanding performance of the RMA. This research will provide a theoretical basis for the order cancellation problem in distributed production settings, and help manufacturers to properly handle canceled orders to reduce resource waste and reschedule the infeasible schemes causing from order cancellation.