Dynamic Uncertainty Study of Multi-Center Location and Route Optimization for Medicine Logistics Company

Multi-center location of pharmaceutical logistics is the focus research, and dynamic uncertainty multi-center a difficult point research. In order to reduce risk cost multi-enterprise, multi-category, large-volume, high-efficiency, nationwide centralized medicine distribution, this study explores best solution for planning delivery logistics. paper, based on idea big data, comprehensive consideration given uncertainties in center location, type, chemical characteristics, quality control (refrigeration monitoring costs), timeliness, other factors. On basis, location- route-optimization model company under constructed. The accuracy algorithm improved by hybridizing fuzzy C-means algorithm, sequential quadratic programming variable neighborhood search combine advantages each. Finally, are verified through high-volume, distribution cases, various combinations three algorithms several rival compared analyzed. Compared with algorithms, hybrid has higher solving path optimization problem