A Multi-Objective Flexible Job Shop Intelligent Scheduling System Based on Soft Dueling Double Deep Q-Networks

With the development of smart factory, the requirements of multi-objective, real-time and intelligent are put forward for the dynamic flexible job shop scheduling problem (DFJSP). In this paper, the flexible job shop intelligent scheduling system is constructed, and the workshop level industrial network topology, scheduling information integration model and its main functions are designed. A soft dueling double deep Q-networks (SDDDQN) method is proposed to solve the DFJSP with random job arrival to minimize the total machine load and maximize the utilization rate of machine tools. Through the gear production scheduling case test, the results show the effectiveness, generalization and timeliness of the flexible job shop scheduling system based on the SDDDQN.