학술논문

Selection Optimization Modeling of Logistics Site and Applications
Document Type
Conference
Source
2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT) ISCTT Information Science, Computer Technology and Transportation (ISCTT), 2020 5th International Conference on. :571-574 Nov, 2020
Subject
Computing and Processing
Economics
Analytical models
Computational modeling
Clustering algorithms
Mathematical model
Optimization
Logistics
selection optimization model of logistics site
improved K-means algorithm
logistics distribution
Language
Abstract
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.