Distribution path optimization of carbon emission-reducing agricultural products in the cold chain from a green economy perspective

Abstract

As people's environmental awareness improves, the development of green economy has become an important goal for countries to achieve sustainable development. The extensive generation of greenhouse gases during the cold chain logistics and distribution process poses a significant challenge to the advancement of the green economy. By utilizing an enhanced genetic algorithm (GA), this research examines the expenses associated with distributing fresh agricultural products via the cold chain and constructs a model for optimizing the path of distribution. Simulation experiments show that the total cost of this model constructed in the study is 2323.94 RMB, which is less than 2623.35 RMB of the traditional path planning model, and the carbon emission is 85 kg less. It proves that the path optimization model constructed by the research has high economic and environmental benefits, and the designed and planned path is more in line with the needs of green economy than the traditional path, which has the potential to minimize carbon emissions during the fresh agricultural product cold chain distribution process while simultaneously promoting sustainable development.

Keywords

• Green economy
• Cold chain
• Path optimization
• GA
• Carbon emissions