Selection Optimization Modeling of Logistics Site and Applications

This paper analyzed the characteristics of logistics distribution site location problem, combined with the impact factors and constraints of logistics distribution link, and constructed the mathematical model of logistics site optimization location. For this model, an improved k-means clustering optimization algorithm is proposed. The algorithm can improves the coordinate division conditions of K-means clustering algorithm, and integrates the global search ability of simulated annealing algorithm, which effectively improves the clustering effect. The experimental results show that the proposed model can accurately express the relationship between logistics cost and site location. Combined with the proposed improved k-means clustering algorithm, the optimal location distribution of economic cost can be obtained.