Network Optimization of Railway Cold Chain Logistics Based on Freight Subsidy

Abstract

The proportion of railway cold chain transportation in the overall cold chain logistics transportation market is relatively small in China. Freight subsidies and cold chain train operations are typically effective approaches to guide the public transit of cold chain cargo flow and grow the railway cold chain transportation market. We analyzed the cost structure of a cold chain transportation network. We established a network optimization model of the railway cold chain logistics based on a freight subsidy and designed an adaptive genetic–simulated annealing algorithm (A-SAGA). Taking the cold chain transportation between the Yangtze river delta urban agglomerations and the Chengdu–Chongqing city group as an example, we determined the optimal cold chain logistics transportation scheme using the traditional genetic algorithm and the A-SAGA. Moreover, we conducted sensitivity analysis on freight subsidies, train travel speeds, soft time windows, and carbon tax rates. The results showed that for medium- and long-distance cold chain transportation, the railway market share increased from 17.55% to 18.75% with an increase in the railway freight rate subsidy share from 0% to 30%. More cold chain goods were transported by rail when the soft time window or the carbon tax rate increased. Moreover, the railway market share increased from 17.55% to 43.75% with an increase in the train travel speed from 60 km/h to 120 km/h. Thus, compared with freight subsidy, increasing the train travel speed is a better approach to improve the competitiveness of railway cold chain logistics.