Resource Scheduling Method for Optimizing the Distribution Path of Fresh Agricultural Products under Low-Carbon Environmental Constraints

Abstract

Aiming at the development concept of relative dispersion of urban multiregional business centers, saving energy, and emission reduction, this article proposes an algorithm for solving the problem of green logistics distribution to fresh agricultural products considering low-carbon and environmental protection, to realize the economic and environmental protection of cold chain logistics. Firstly, we comprehensively consider the fixed costs of delivery vehicles, transportation costs, damage costs of fresh agricultural products, cooling costs, carbon emissions costs, and penalty costs due to service time windows that do not meet customer requirements as the objective function to construct green logistics distribution location-routing optimization model. Then, Tent chaotic perturbation method is introduced to optimize the genetic algorithm and an improved genetic algorithm is used to solve the distribution location-routing optimization model to obtain the best scheme. Finally, the proposed algorithm is verified experimentally based on the MATLAB simulation platform. Experimental results show that the total distance and total cost of the distribution plan obtained by the proposed algorithm are 128.96 km and 12,593 yuan, respectively, which are superior to other comparison algorithms and can be used as a reference for logistics enterprises' distribution decision-making.