Application Of Sparrow Search Algorithm in Cold Chain Low Carbonization Logistics

Abstract

Driven by consumer upgrades and national policies, the cold chain logistics industry has experienced rapid development, accompanied by increased expenditure of energy and carbon emissions. To achieve energy savings, emission reductions, and overall cost reduction in the cold chain logistics industry, this article establishes an optimization model for optimizing transportation routes, taking into account carbon emission costs, refrigeration costs, and time penalty costs. The objective is to comprehensively consider reducing refrigeration costs and time penalty costs throughout the entire phase of cold chain logistics, aiming to minimize the total cost for logistics companies during actual delivery processes. The improved Sparrow Search Algorithm (SSA) is employed to solve the optimization problem. The results of the case study analysis validate the applicability and superiority of the improved SSA for route optimization problems, as it demonstrates fast convergence speed and strong search capabilities.