The globalization of the economy and trade has made the transportation industry flourish, and the traffic demand is growing. Under this trend, energy consumption is increasing and environmental pollution is becoming more and more serious, so the development of “low-carbon transportation” is inevitable. Intermodality is a green transportation method that reduces transportation costs, shortens transportation time, improves transportation quality, reduces road congestion and is environmentally friendly. It can reduce carbon emissions and noise pollution while improving energy efficiency. Therefore, strengthening the use of intermodality can significantly reduce carbon dioxide emissions, thereby reducing the greenhouse effect. In the present study, carbon emissions are added to the intermodality route study, and an intermodality path selection model in a low-carbon environment is established. Through the use of genetic algorithms and step-by-step method to solve this problem, we find the best low-carbon transportation methods and routes. It has practical application value, enabling decision makers to balance the economic interests of the company while making decisions and to meet the government’s carbon dioxide emission limitations.

中文翻译：

---

考虑碳排放多任务的多式联运路径优化模型与算法

经济和贸易的全球化使交通运输业蓬勃发展，交通需求日益增长。在这种趋势下，能源消耗越来越大，环境污染也越来越严重，“低碳交通”的发展势在必行。多式联运是一种降低运输成本、缩短运输时间、提高运输质量、减少道路拥堵和环境友好的绿色运输方式。它可以减少碳排放和噪音污染，同时提高能源效率。因此，加强多式联运的使用可以显着减少二氧化碳排放，从而减少温室效应。在本研究中，碳排放被添加到多式联运路线研究中，建立低碳环境下的多式联运路径选择模型。通过使用遗传算法和循序渐进的方法来解决这个问题，我们找到了最好的低碳交通方式和路线。具有实际应用价值，使决策者在决策的同时兼顾公司的经济利益，满足政府对二氧化碳排放的限制。