低碳环境下的多式联运路径优化研究

发布时间：2018-07-24 13:04

【摘要】：随着电子商务的飞速发展和“互联网+”的强力推进,物流作为商流的后继者和服务者,在提高社会经济效益中举足轻重。多式联运能够根据不同运输方式的特点,合理安排运输方式的衔接,不仅能够实现物流效率的提高,而且对社会经济效益的提高具有显著作用。因此,在生态问题日益严峻的今天,低碳环境下多式联运路径优化研究具有重要的现实意义和理论意义。在现有的多式联运路径优化研究中,较少考虑到货损率和非正常工作时间对路径选择的影响,同时碳交易价格没有考虑供需关系的影响。然而,在追求质量与实效的现代物流中,货损时有发生,若货物到达中转节点的时间为非正常工作时间时,为保障运输过程的实效性,多式联运经营人往往会承担额外的转运费用。另外,现有研究在对多目标到单目标进行转化时,大多根据因素的重要程度进行权重赋值,带有一定的主观性。因此,本文考虑货损率的现实影响,基于系统工程理论,利用基于信息熵的TOPSIS方法和遗传算法,站在多式联运经营人的角度分别建立了低碳多式联运路径优化的多目标模型和单目标模型。对于多目标模型,为消除主观因素对权重赋值造成的影响,本文运用熵值法确定指标权重。利用基于信息熵的TOPSIS方法与遗传算法结合,把个体与理想解的接近程度作为适应度函数进行个体的优劣选择。通过对不同货损率约束下的联运方案集进行对比分析,验证了算法设计的有效性和合理性。对于单目标模型,本文在时间窗成本中考虑了中转节点处非正常工作时间可能产生的额外转运费用;在碳排放成本中考虑了碳税、变动交易价格下的碳交易、碳交易背景下的碳税三种情况,建立了对应的总成本最小的单目标路径优化模型,运用遗传算法进行案例求解,分析了不同的碳税税率、碳排放权配额、时间窗对路径选择的影响,验证了模型和算法的可行性和有效性。本文提出的模型和算法,为多式联运经营人在复杂的环境下制定合理的多式联运路径优化方案提供了一定的决策依据,对社会经济效益的提高、环境的可持续发展具有重要的理论意义和现实意义。
[Abstract]:With the rapid development of electronic commerce and the strong promotion of Internet, logistics, as a successor and service provider of commercial flow, plays an important role in improving social and economic benefits. According to the characteristics of different modes of transport, multimodal transport can arrange the connection of transportation modes reasonably, which can not only improve the efficiency of logistics, but also play an important role in the improvement of social and economic benefits. Therefore, in the increasingly serious ecological problem today, the research of multimodal transport path optimization in low carbon environment has important practical and theoretical significance. The influence of damage rate and abnormal working hours on route selection is seldom considered in the existing multimodal transport route optimization studies, and the effect of supply and demand is not taken into account in carbon trading price. However, in the pursuit of quality and effectiveness of modern logistics, damage occurs from time to time. If the time of arrival of the goods is abnormal working time, in order to ensure the effectiveness of the transportation process, Multimodal transport operators often bear additional freight charges. In addition, in the transformation of multi-objective to single-objective, most of the existing studies assign weights according to the degree of importance of factors, which is subjective to a certain extent. Therefore, based on the theory of system engineering, the TOPSIS method based on information entropy and genetic algorithm are used in this paper. The multiobjective model and the single objective model of path optimization for low carbon multimodal transport are established from the perspective of multimodal transport operator. For the multi-objective model, in order to eliminate the influence of subjective factors on the weight assignment, the entropy method is used to determine the index weight. By combining the TOPSIS method based on information entropy with genetic algorithm, the proximity between individual and ideal solution is regarded as fitness function to select individual's merits and demerits. The validity and rationality of the algorithm are verified by comparing and analyzing the combined transport schemes with different damage rates. For the single-objective model, this paper takes into account the extra transshipment cost caused by the abnormal working hours at the transfer node in the time window cost, the carbon tax in the carbon emission cost, and the carbon trading under the variable transaction price. Under the background of carbon trading, a single objective path optimization model with minimum total cost is set up, and a case is solved by genetic algorithm, and different carbon tax rates and carbon emission quota are analyzed. The influence of time window on path selection verifies the feasibility and validity of the model and algorithm. The model and algorithm proposed in this paper provide a certain decision basis for the multimodal transport operators to formulate a reasonable multimodal transport route optimization scheme under the complex environment, and improve the social and economic benefits. The sustainable development of environment has important theoretical and practical significance.
【学位授予单位】：河南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：X196;F259.2

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