Abstract: To identify the effects of low-carbon policies and road congestion on multimodal transportation path selection, multimodal transportation route selection models with congestion considered under different low-carbon polices are constructed, which further quantify the influence of congestion on system carbon emissions after considering the impact of congestion on transport time. A genetic algorithm based on elitist strategy and immigrant strategy is designed for those integer programming models. At last, numerical experiments are provided to explore the effects of four kinds of carbon emission policies(mandatory emission, carbon tax, carbon trade and carbon offset)on carbon reduction, congestion mitigation and costs of multimodal transportation. Result show that more reasonable routing decisions can be obtained when the influence of congestion on system carbon emissions is considered. In addition, the combination of several emission policies based on mandatory carbon emission policy can better reduce carbon emissions, alleviate road congestion and promote the implementation of multimodal transportation. The models may provide theoretical bases for the government to make reasonable multimodal low-carbon policies, and for the enterprises to make reasonable routing decisions.

Key words: route selection problem, multimodal transportation, low-carbon policies, congestion, GA

摘要： 为明确低碳政策及道路拥堵对多式联运路径选择的影响,构建了不同碳排放政策下考虑道路拥堵的多式联运路径选择模型。模型在考虑拥堵对运输时间影响的基础上进一步量化其对系统碳排放的作用效果。针对此类整数规划模型,设计了基于保优策略和移民策略的遗传算法进行求解。最后,通过算例探讨强制排放、碳税、碳交易及碳补偿四种碳排放政策对多式联运减排、缓解拥堵及成本的影响。结果表明考虑道路拥堵对运输碳排放的影响可得到更加合理的路径决策,且以强制碳排放政策为主的多种政策组合能更好的降低碳排放、缓解道路拥堵并促进多式联运推广。本模型可为政府制定合理的多式联运低碳政策以及企业制定合理的路径决策提供理论依据。

关键词: 路径选择问题, 多式联运, 低碳政策, 拥堵, 遗传算法