低碳约束下多式联运路径优化问题研究

发布时间：2018-04-29 12:54

  本文选题：多式联运 + 碳足迹　； 参考：《浙江工商大学》2017年硕士论文

【摘要】：因人类大量排放二氧化碳等温室气体,全球许多地方气温接连异常上升,已对人类社会产生严重的负面影响。物流行业作为碳排放大户,必须进行有效的绿色转型。实践经验显示,多式联运能够有效促进物流行业的低碳化发展。目前,我国公路物流运输占比较高,能源消耗大,环境清洁性差;铁路、水路等低碳物流运输方式的运力未被充分利用。同时,我国低碳约束下的多式联运理论研究仍处于起步阶段,其中许多问题有待研究解决。本文以"低碳约束下的多式联运"为对象开展研究,具体工作如下:第一,碳排放最小化为目标的多式联运路径优化模型构建。模型分析了多式联运过程中干线阶段的运输碳排放以及因运输方式变更引起的转运碳排放,考虑服务时间限制,并以总的碳排放量最小为目标。求解过程中,本文同时对运输路线选择和运输方式组合进行考虑,设计改进的遗传算法进行算例分析。结果表明,在多式联运过程加大铁路、水路运输有利于整体碳排放的降低;针对时效要求高的运输任务,可以通过部分采用灵活快速的公路运输进行提速。第二,考虑碳排放、时间和费用的多目标多式联运路径优化模型构建。企业实际运营过程中,运输时效性是客户服务满意度的一个重要指标,成本是企业生存必须考虑的重要因素。为了实现企业绿色发展、降低运输过程碳排放,采取多式联运,而各个目标之间存在二律背反关系,如何在碳排放、时间和费用三者之间进行平衡求解,是该问题的难点。目前研究,对于多目标多式联运的求解,一般通过加权法或将碳排放和时间因素转化为费用成本,即将多目标转化为单一目标,再进行求解。权重的赋值和因素转化具有很强的主观性,不利于多目标问题的真正求解。本文构建考虑碳排放、时间和费用的多目标多式联运路径优化模型,采用NSGA-Ⅱ快速非支配排序算法求解模型,得到运输路线和运输组合的帕累托最优。通过算例分析,证明模型的可行性。第三,市内多式联运末端配送实现的碳足迹定量研究。目前多式联运研究的重点多为多式联运的干线运输,对市内多式联运领域的研究比较少。本文对市内多式联运末端配送实现的碳足迹情况开展讨论,对运输方式与配送模式进行组合分析,并以实证数据进行定量研究,提出使用清洁能源与快递服务点、快递储藏柜等新型配送模式组合实现市内末端配送的建议。
[Abstract]:Due to the massive emission of carbon dioxide and other greenhouse gases, the temperature in many parts of the world has been rising abnormally, which has had a serious negative impact on human society. Logistics industry as a large carbon emissions, we must carry out an effective green transformation. Practical experience shows that multimodal transport can effectively promote the low-carbon development of the logistics industry. At present, the road logistics transportation in China is relatively high, the energy consumption is large, the environment is not clean, and the capacity of low-carbon logistics transportation such as railways and waterways has not been fully utilized. At the same time, the theory of multimodal transport under low carbon constraints in China is still in its infancy, and many problems need to be solved. In this paper, "low carbon constrained multimodal transport" is studied. The main work is as follows: firstly, the path optimization model of multimodal transport with carbon emission minimization as its goal is constructed. The model analyzes the transport carbon emissions in the main line stage and the transshipment carbon emissions due to the change of the mode of transport in the multimodal transport process, considering the service time limit, and aiming at the minimum total carbon emissions. In the process of solving the problem, the selection of transportation route and the combination of transportation modes are considered in this paper, and the improved genetic algorithm is designed for example analysis. The results show that waterway transportation is beneficial to the reduction of overall carbon emission in the process of multimodal transport, and can be increased partly by flexible and rapid road transportation for the transport task with high efficiency. Second, multi-objective multimodal transport path optimization model considering carbon emissions, time and cost. Transportation timeliness is an important index of customer service satisfaction and cost is an important factor that must be taken into account in the process of enterprise operation. In order to realize the green development of the enterprise, reduce the carbon emission in the transportation process and adopt multimodal transport, there is a two-law inverse relationship between each target. How to balance the carbon emission, time and cost is the difficulty of this problem. At present, the solution of multiobjective multimodal transport is usually solved by weighting method or converting carbon emissions and time factors into cost, that is to say, multi-objective is transformed into a single objective, and then solved. The assignment of weights and the transformation of factors are highly subjective, which is not conducive to the real solution of multi-objective problems. In this paper, a multi-objective multimodal transport path optimization model considering carbon emission, time and cost is constructed, and the model is solved by NSGA- 鈪，

本文编号：1820018