考虑碳排放因素的车辆路径优化建模研究
发布时间:2018-01-15 07:38
本文关键词:考虑碳排放因素的车辆路径优化建模研究 出处:《重庆交通大学》2015年硕士论文 论文类型:学位论文
【摘要】:伴随着全球经济一体化的深入,中国经济迎来快速发展的春天,与此同时其能源消耗也呈现日益增长的趋势。其中,中国碳排放量从1980年的14.5亿吨急剧增长到2013年的100亿吨而位居全球第一,占据全球总排放量的29%。研究显示,物流配送已经成为全球碳排放的重要来源之一,其产生的温室气体占据全部份额的14%。相比美国12%和欧盟11%的份额,我国物流业温室气体排放占据总温室气体高达19%。因此,研究考虑碳排放因素的车辆路径问题以降低我国物流运输行业碳排放变得至关重要。本篇文章研究的重点是考虑碳排放因素下车辆路径模型和优化方法,具体的研究内容和创新之处如下所示:首先,针对计算货运车辆的碳排放量需要,比较分析碳排放的计算模型;考虑到计算的简便性和可操作性,适当简化处理计算模型。针对物流企业可能参与到碳交易中,同时面临碳排放权的买卖操作和碳惩罚的情况,研究适用于物流配送企业的带碳惩罚的碳交易机制和模型,此外还分析碳交易机制的波动对物流配送构成的影响。其次,针对研究的车辆路径问题,建立带碳排放和时间窗的多目标整数规划模型;考虑到求解模型的复杂性,结合聚类分析方法、扫描算法和两边逐次修正算法来设计新的混合遗传算法。通过聚类分析技术可以根据客户的离散情况进行分类,减少算法的无效搜索;其次,采用扫描算法可以对同类客户进行快速排序,避免产生适应度太差的个体;最后,使用两边逐次修正算法可以对优化后的子路径进行再度优化,从而提高算法的求解性能。为验证设计算法的性能,采用标准算例对算法的有效性和可靠性进行测试。最后,结合重庆天友乳业股份有限公司的物流配送案例,验证本文建立的考虑碳排放因素的车辆路径模型和设计的混合遗传算法。同时根据本案例,分别讨论在单车型、混合车型、不同比例下碳交易量、不同碳交易价格和碳惩罚价格对物流配送的影响,此外还对比其他启发式算法验证设计的混合遗传算法实用性和稳定性。本文的主要贡献是,第一,总结物流配送车辆的碳排放计算模型,确定适合本文的碳排放计算方式,其次建立碳交易机制和讨论对物流配送的影响。第二,针对问题建立多目标带碳排放和时间窗的车辆路径整数规划模型,针对求解模型的复杂性设计出混合遗传算法,同时采用算例验证了模型和算法。第三,通过案例进一步验证构建的考虑碳排放的车辆路径模型和求解算法。
[Abstract]:Along with the deepening of global economic integration, China economy ushered in the rapid development of the spring at the same time, the energy consumption also shows an increasing trend. Among them, carbon emissions China from 1980 14.5 tons of rapid growth of 100 tons by 2013 and ranked first in the world, accounting for the total global emissions according to the 29%. study shows that the logistics distribution has one of the important sources of global carbon emissions of greenhouse gases, the share of 14%. accounted for 12% compared to the United States and EU 11% share, occupy the total greenhouse gas emissions of greenhouse gases in China's logistics industry is as high as 19%. so, considering the vehicle routing problem of carbon emission factors to reduce China's carbon emissions becomes crucial for transportation and logistics industry the focus of this article. The research is to consider the carbon emission factors under the vehicle routing model and optimization method, the specific research contents and innovations are as follows First, for carbon emissions calculation of freight vehicles, comparison analysis and calculation model of carbon emission; considering the computational simplicity and operability, a simplified calculation model for logistics enterprises may be involved in carbon trading, carbon emissions are buying and selling operations and carbon punishment at the same time, research suitable for logistics enterprises with carbon carbon trading mechanism and model of punishment, in addition to the analysis of effects of carbon trading mechanism fluctuation on logistics distribution structure. Secondly, according to the study on vehicle routing problem, a multi-objective integer programming model with carbon emissions and time window; considering the complexity of solving the model, combined with clustering analysis method, scanning algorithm and successive correction algorithm on both sides to design the new hybrid genetic algorithm. Through clustering analysis technology can be classified according to the discrete situation of customers, reduce the invalid search algorithm ; secondly, using scanning algorithm can quickly sort of similar customers, avoid bad individual fitness; finally, the use of two successive correction algorithm can be re optimization of the optimized sub path, so as to improve the capability of the algorithm. To validate the performance of algorithm design, using standard examples to test the effectiveness the algorithm and reliability. Finally, combined with the logistics distribution case of Chongqing Tianyou dairy Limited by Share Ltd, considering the hybrid genetic algorithm to vehicle routing model and design of carbon emission factors to verify this. At the same time according to the case, are discussed respectively in the single models, mixed models, carbon trading volume ratio, the influence of different carbon trading price the price of carbon and punishment of logistics and distribution, in addition, compared with other heuristic algorithms and verify the design of the hybrid genetic algorithm is practical and stable. The main contribution of this paper Is the first, summarize the logistics vehicle emissions calculation model, calculation method to determine the suitable carbon emissions, followed by establishing carbon trading mechanism and Discussion on logistics distribution vehicle routing. Second integer programming model to solve the problem of multi target with carbon emissions and time windows, designed to solve the model according to the complexity of hybrid the genetic algorithm, the results verify the model and algorithm. Third, through the case further verification considering vehicle routing model and algorithm for the construction of carbon emissions.
【学位授予单位】:重庆交通大学
【学位级别】:硕士
【学位授予年份】:2015
【分类号】:U492.22
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