A Dynamic Optimization Method of Material Distribution Intervals and Quantity for High-end Equipment Manufacturing

To address the logistics problems faced by high-end equipment manufacturers in their two-stage supply chain, this study proposes an optimization strategy for material distribution intervals and quantities. The strategy is based on an improved Mayfly algorithm. These problems include difficulties in accurately responding to production demands, high logistics distribution costs, and low material quality. We have established a two-stage collaborative optimization model of material distribution. This model is adapted to production takt time and its intelligent algorithm. Firstly, we construct a two-stage material distribution interval and quantity optimization model. This model incorporates the total logistics cost of the two-stage supply chain as the optimization objective. It uses Just-in-time delivery and delivery time as constraints. It also considers the complexity of multi-supplier proportional supply. The model is built from multi-supplier to the manufacturer’s warehouse and from the manufacturer’s warehouse to the assembly line side, taking into account material quality. Then, based on this model, we propose an improved Mayfly algorithm. This improved algorithm integrates chaotic maps and adaptive inertia weight. These enhancements aim to improve the optimization ability and convergence speed of the Mayfly algorithm. Finally, we verify the feasibility and effectiveness of the model and algorithm. We conduct an example application under different production takt times. The results demonstrate that the developed model and algorithm have competitive performance in addressing the studied problems, achieving significant reductions in material distribution costs.