An Empirical Study on Optimization of Multipath Cold-Chain Delivery Network

Distribution of food ingredients for restaurants generally involves the optimization of multi-input and multi-output logistics system of the secondary distribution network. Based on the location distribution of 6 restaurants and the layout of 3 front-end warehouses determined by hierarchical clustering analysis algorithm, the innovative "time-distance saving algorithm", considering the influence of distance and time at the same time, is designed to optimize the design and empirical research on the real delivery routes from the food cold chain distribution center to the front-end warehouses. Using “auto navigation" and comprehensively considering the weighting factors of delivery time and delivery distance, the satisfactory solution of the distribution of multiple actual delivery routes was obtained. The results showed that the total delivery distance and time saving of the optimized cold chain delivery network are significantly better than those of traditional saving algorithms.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-01
DOI
https://doi.org/10.5281/zenodo.13358817
Primary Topic
Food Supply Chain Traceability
Type
article
Field-Weighted Citation Impact
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article

An Empirical Study on Optimization of Multipath Cold-Chain Delivery Network

Zenodo (CERN European Organization for Nuclear Research)
Food Supply Chain Traceability
article

An Empirical Study on Optimization of Multipath Cold-Chain Delivery Network

article en

Abstract

Distribution of food ingredients for restaurants generally involves the optimization of multi-input and multi-output logistics system of the secondary distribution network. Based on the location distribution of 6 restaurants and the layout of 3 front-end warehouses determined by hierarchical clustering analysis algorithm, the innovative "time-distance saving algorithm", considering the influence of distance and time at the same time, is designed to optimize the design and empirical research on the real delivery routes from the food cold chain distribution center to the front-end warehouses. Using “auto navigation" and comprehensively considering the weighting factors of delivery time and delivery distance, the satisfactory solution of the distribution of multiple actual delivery routes was obtained. The results showed that the total delivery distance and time saving of the optimized cold chain delivery network are significantly better than those of traditional saving algorithms.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 52%
Food Supply Chain Traceability
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