Dynamic Uncertainty Study of Multi-Center Location and Route Optimization for Medicine Logistics Company
Mathematics
; 10(6):953, 2022.
Article
in English
| ProQuest Central | ID: covidwho-1765783
ABSTRACT
Multi-center location of pharmaceutical logistics is the focus of pharmaceutical logistics research, and the dynamic uncertainty of pharmaceutical logistics multi-center location is a difficult point of research. In order to reduce the risk and cost of multi-enterprise, multi-category, large-volume, high-efficiency, and nationwide centralized medicine distribution, this study explores the best solution for planning medicine delivery for the medicine logistics. In this paper, based on the idea of big data, comprehensive consideration is given to uncertainties in center location, medicine type, medicine chemical characteristics, cost of medicine quality control (refrigeration and monitoring costs), delivery timeliness, and other factors. On this basis, a multi-center location- and route-optimization model for a medicine logistics company under dynamic uncertainty is constructed. The accuracy of the algorithm is improved by hybridizing the fuzzy C-means algorithm, sequential quadratic programming algorithm, and variable neighborhood search algorithm to combine the advantages of each. Finally, the model and the algorithm are verified through multi-enterprise, multi-category, high-volume, high-efficiency, and nationwide centralized medicine distribution cases, and various combinations of the three algorithms and several rival algorithms are compared and analyzed. Compared with rival algorithms, this hybrid algorithm has higher accuracy in solving multi-center location path optimization problem under the dynamic uncertainty in pharmaceutical logistics.
Mathematics; uncertainty; medicine distribution; FCM-SQP-VNS hybrid algorithm; Accuracy; Customer satisfaction; Quality control; Construction costs; Quadratic programming; Cold storage; Pharmaceutical industry; Pharmaceuticals; Efficiency; Optimization models; COVID-19; Mathematical programming; Big Data; Research methodology; Medicine; Route optimization; Carbon; Genetic algorithms; Blood banks; Design; Search algorithms; Linear programming; Logistics; Inventory; Operating costs
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Language:
English
Journal:
Mathematics
Year:
2022
Document Type:
Article
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