Optimized Genetic Algorithm Based on Hierarchical Scheduling Criteria for Workshop Information Scheduling System

The workshop information scheduling system is a widely used management tool in the manufacturing industry. It can reasonably schedule and optimize production tasks in the workshop to improve production efficiency and reduce costs. Accurately scheduling and optimizing tasks is crucial in a workshop information scheduling system. Therefore, a mathematical model is first constructed for the workshop information scheduling system. To minimize the maximum completion time, a pointer network is introduced to improve the initial population quality of the genetic algorithm. The iterative optimization is carried out using a restart mechanism. Meanwhile, by introducing a hierarchical scheduling algorithm, complex production scheduling is divided into different levels for processing. This hierarchical scheduling algorithm achieves efficient workshop information scheduling through pre-scheduling and lean scheduling. The results show that the average delay penalty of the proposed method in the Kacem05 is only 212.3. Compared to the other two algorithms, it has decreased by 11.2 and 476.9, respectively. The bottleneck utilization rate is close to 100%. In addition, the average calculation time of this algorithm is only 65.8 s. Compared to the GA, it reduces 673.9 s. The hierarchical scheduling method based on pointer network hybrid genetic algorithm has significant performance advantages and practical application effects, providing an effective solution for optimizing the workshop information scheduling system.