In order to improve the performance and change the current situation of the cost minimization model widely used in the cold chain logistics distribution process, a multi-objective optimization model based on cost, carbon emissions and customer satisfaction is proposed. Considering the characteristic of this proposed optimization model, we design an improved ant colony algorithm with a multi-objective heuristic function to solve it, termed as ACOMO. Experimental results show that the proposed ACOMO can effectively solve the vehicle routing problem of the multi-objective optimization model, and outperforms the classic ant colony algorithms, resulting in more Pareto optimal solutions. It offers an environmentally friendly distribution solution for the problem. Specifically, the distribution path obtained by the improved ant colony algorithm manages to achieve the above multiple goals, including reduction of distribution costs and carbon emissions, and improvement of customer satisfaction. In addition, compared with a single-target model that only provides one single distribution route to cost minimization, multi-objective optimization can provide a variety of distribution route options for logistics companies in practice. Finally, through the sensitivity analysis of temperature changes and cargo damage coefficients, the proposed system successfully provides reference for the optimization of the path of cold chain logistics enterprises, and promotes logistics enterprises to effectively arrange their work and to be more socially responsible. INDEX TERMS Cold chain logistics, path optimization, multi-objective optimization, carbon constraints, customer satisfaction.
Government subsidy can greatly encourage supply chain enterprises to reduce carbon emissions. To quickly occupy the market, supply chain enterprises form alliances. However, enterprises in the alliance have speculative psychology, and the impact of such free riding behavior on the carbon emissions reduction willingness of supply chain enterprises is still unclear. In this article, government subsidies and free riding behavior parameters are introduced to build a carbon emissions reduction decision model for the government, manufacturers, and suppliers, and the impact of government subsidies and free riding behavior on the decision making of supply chain enterprises is analyzed through evolutionary game theory. The analysis shows that government subsidies have an incentive effect on carbon emissions reduction of supply chain enterprises. After the market stabilizes, even if the government subsidies are gradually withdrawn, the carbon emissions reduction of supply chain enterprises still converges to Pareto optimal equilibrium. The influence of free riding behavior on supply chain enterprises depends on the carbon emissions reduction profit. When the carbon emissions reduction profit is different, the decision of manufacturers and suppliers will be different. The above conclusions provide a reference for governments to strengthen control or enterprises to make decisions on carbon emissions reduction.
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