Research on Flexible Job Shop Scheduling based on an Improved Dung Beetle Optimization Algorithm

To tackle the challenges of job delivery times with buffer periods in actual orders, this study proposes an optimization strategy based on job weights, aimed at minimizing delivery times.A novel method has been developed for the conversion of job weights, which integrates the urgency associated with job delivery deadlines. This approach prioritizes the optimization of optional machine scheduling and the coordination of multi-process arrangements to mitigate waiting times in buffer zones. An Improved dung beetle optimization algorithm is designed specifically for the flexible job shop scheduling problem, targeting the minimization of delivery times. This approach utilizes a hybrid population initialization strategy to generate a high-quality initial population and incorporates a multipoint mutation strategy to enhance the diversity of transitions between individual positions and scheduling solutions, thereby improving accuracy in identifying optimal solutions. Additionally, a spiral search strategy is integrated to bolster local search capabilities. Comparative tests demonstrate that the improved algorithm significantly enhances both solving speed and accuracy.