Disruption management of flexible job shop scheduling considering behavior perception and machine fault based on improved NSGA-II algorithm

Abstract

Aiming at the disturbance event of single machine sudden failure in the initial job scheduling of flexible job shop, the dissatisfaction of customers, enterprises and labor workers is quantified using the unascertained theory, and a scheduling interference management model considering the characteristics of three parties is constructed. The NSGA-II algorithm is improved using the strategy of close relative crossover and mutation, and the efficient solution to the flexible job shop scheduling problem is realized. The example shows that the interference management model proposed in this paper can better reduce disturbance of the disturbance events compared with rescheduling, AOR rescheduling and full right shift scheduling, which can restore the normal operation of the processing and manufacturing system to realize the coordination of different stakeholders.