Abstract
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.
Highlights
With the improvement in the living standards of consumers and the change of consuming ideas, the cold chain logistics of the fresh products has developed rapidly in recent years, which brings higher requirements for the distribution process to the logistics companies
Customer satisfaction of the classic ant colony algorithm has been in a higher position, while the improved ant colony algorithm further increases it by 0.71%
We will analyze the table in detail.The specific distribution routes are shown in the following FIGURES: The Pareto optimal solution sets are obtained from the solutions of all multi-objective optimization problems that are pertinent to lower cost, lower carbon emission, and higher customer satisfaction
Summary
With the improvement in the living standards of consumers and the change of consuming ideas, the cold chain logistics of the fresh products has developed rapidly in recent years, which brings higher requirements for the distribution process to the logistics companies. Reducing energy consumption and carbon emissions have become an inevitable trend in the development of the logistics industry [7], [8] In view of these factors that need to be considered in cold chain logistics distribution, this paper proposes a multi-objective optimization model. It aims to improve the customer satisfaction while reducing costs and carbon emissions during the distribution process. The penalty cost for late arrival is higher than that of early arrival When such a delivery is a concern, we need to take into account several factors such as carbon emissions, customer satisfaction, and minimization of the costs to find the optimal distribution path besides the requirements of goods, refrigerated vehicle weight, and time window.
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