Demand-predictive storage assignment mechanism for flower auction centers

As the number of daily transactions continues to increase, congestion frequently occurs in flower auction centers. Put system is widely applied in intralogistics operations, which includes distribution and redistribution areas. The uncertain arrivals of demands pose significant challenges for the efficient intralogistics operations in flower auction center. In order to improve performance of the put system, this study newly designs a demand-predictive storage assignment (DSA) mechanism in which uncertain demands are forecasted by constructing $A/F $A/F ratio time series of each customer. Based on the demand forecasts, the customer locations within the distribution area and the number of locations within the redistribution area are easily determined. Furthermore, a paired redistribution strategy is proposed that enables two customers to share a staging block. A simulation experiment bed is constructed based on a real-life case. The experimental results indicate that the $A/F $A/F forecasting method outperforms other demand forecast methods in literature with lower forecasting error, and the proposed DSA mechanism reduces the total travel distance compared with the closest open location.