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Disruption Management of Multi-objective Flexible Job-Shop Scheduling Problem

Aiming at the problem that the initial scheduling scheme needs to be changed due to the disturbance event in the production process, based on the prospect theory, a disruption management model considering the degree of disturbance perception of the three actors of the customer, the enterprise manager and the workshop worker is proposed. An improved multi-objectives method is proposed to solve the dynamic Job-shop scheduling problem based on disruption management. A quantum genetic algorithm for adaptively adjusting the rotation angle is proposed. The randomness and stability tendency of the cloud model are used to adaptively adjust the rotation angle. Numerical experiments show that the algorithm has good performance for solving disruption management problems.