Multi-objective Optimization of Cross-Docking Logistics System under Stochastic Demand

In order to enhance the adaptivity of cross-docking logistics (CDL) to stochastic market demand, a multi-objective stochastic programming model was established. Taking both local and global interests into account and considering the factors such as random demand, inventory, distribution, and original orders, This model aims at improving the confidence level of final orders to meet the stochastic demand, increasing the vehicle loading rate, and reducing the total operation cost, and To solve the model, a multi-objective fitness function was constructed and normalized, and an adaptive genetic algorithm was designed. The result of a case study shows that, compared with the original orders, the final orders dealt with by this model can increase the confidence level meeting stochastic demand and vehicle loading rate by 3.59% and 12.71%, respectively, and reduce the average total cost per day by 631 845 yuan, a decline of 13.73%.