Research on cold chain logistics optimization model considering low-carbon emissions

Abstract

Cold chain logistics distribution orders have increased due to the impact of COVID-19. In view of the increasing difficulty of route optimization and the increase of carbon emissions in the process of cold chain logistics distribution, a mathematical model for route optimization of cold chain logistics distribution vehicles with minimum comprehensive cost is established by considering the cost of carbon emission intensity comprehensively in this paper. The main contributions of this paper are as follows:1.An improved hybrid ant colony algorithm is proposed, which combined simulated annealing algorithm to get rid of the local optimal solution.2. Chaotic mapping is introduced in pheromone update to accelerate convergence and improve search efficiency. The effectiveness of the proposed method in optimizing cold chain logistics distribution path and reducing costs is verified by simulation experiments and comparison with the existing classical algorithms.

Research on VRP Model Optimization of Cold Chain Logistics Under Low-Carbon Constraints

“…VRP refers to formulating distribution rules for distribution vehicles, specifying optimization goals (such as minimum cost), and meeting corresponding constraints (such as not exceeding in terms of vehicle load and minimum delivery vehicles) (S. Wang et al, 2017). The delivery route and transportation vehicles are dispatched reasonably and effectively, so as to realize the most optimized dispatching plan (Tao et al, 2023). Effective vehicle routing scheduling can play a positive role in reducing distribution costs, increasing economic benefits, and saving time, and the transportation paths obtained with different objective functions are also different.…”

Multi-Objective Cold Chain Path Optimization Based on Customer Satisfaction

“…There are many studies on the path optimization of cold chain distribution of fresh agricultural products by scholars at home and abroad. To overcome the problem, Zheng et al [1] developed a cold chain route optimization model that takes into account intermodal transportation and customer happiness, and he referred to an enhanced particle swarm optimization technique; Xiong [2] modified the ant colony optimization method by include transit time, transportation cooling, and road variables; Peng [3] investigates the expenses as well as efficacy of cold chain transportation, develops a fresh food cold chain transportation model, and determines the ideal path using an enhanced genetic algorithm; Tao et al [4] developed a cold chain logistics distributing truck routing model with the lowest total cost while accounting for carbon emissions, included chaotic mapping into pheromone updating, and paired it with the simulated annealing approach to reach the local optimal solution.…”