多车型辆路径问题研究与应用

发布时间：2018-04-09 12:39

本文选题：车辆路径问题　切入点：多车型　出处：《西南交通大学》2014年硕士论文

【摘要】：随着全球气候变暖,减少能耗、控制碳排放变得日益重要。物流作为能源消耗量较大的行业,应肩负起节能减排的责任,倡导低碳物流,改变物流粗放低效率的运作模式。配送是物流的一个重要环节,其运输过程中存在着返程或起程空驶、交叉运输、迂回运输、重复运输等不合理现象,燃油的消耗量也就无法忽略不计,这就需要对配送路线进行合理优化,并且优化过程中应更多考虑加入减少能耗作为目标之一。而在实际配送中,车辆类型不止一种,不同车型还具有不同的装载能力、不同的固定成本、不同的行驶距离等特点,多车型的车辆路径问题更具有现实意义。因此考虑能耗的多车型车辆路径问题成为本文研究的重点,也更具有理论和实践上的指导意义。本文首先总结归纳了国内外多车型车辆路径问题研究现状,并重点分析了多车型车辆路径问题的构成要素、数学模型和求解算法,尤其是对求解多车型问题的算法进行了分析,遗传算法因其强鲁棒性、全局收敛、易于操作以及较少应用于多车型求解中而成为本文选择的算法。然后结合低碳物流节能减排的思想,将与车型相关的能耗成本和固定成本之和作为优化目标,建立起多车型低耗车辆路径问题(Fleet Size and Mix Vehicle Routing Problem with Energy Minimizing, FSMVRPEM),并设计改进遗传算法进行求解,在基准测试上验证算法的可行性和有效性,并取得了较好的效果。最后将多车型低耗车辆路径问题应用于快速消费品的配送中心,由于其零售网点分布密集、需求量小但稳定的特点,当前物流中心采用固定路线的配送方案。针对于此本文从整体出发,选取市区作为优化范围,结果不仅减少了车辆使用,还提高了服务水平,是一种较为合理的优化方案。因模型数据获取的方便性以及求解算法的可行性和有效性,是车辆调度安排和线路优化较好的决策工具。对于算法中实现车型选择的直观性和高效性还需要进一步探讨,能否将多车型低耗车型路径问题模型应用于实际中求解大规模的顾客点的问题还需要进一步的研究。
[Abstract]:With global warming, reducing energy consumption, carbon emissions control has become increasingly important.Logistics, as an industry with large energy consumption, should shoulder the responsibility of energy saving and emission reduction, advocate low-carbon logistics, and change the operation mode of extensive and inefficient logistics.Distribution is an important part of logistics. In the process of transportation, there are unreasonable phenomena such as return or departure empty driving, cross transportation, roundabout transportation, repeated transportation, etc., so the consumption of fuel can not be ignored.Therefore, it is necessary to optimize the distribution route reasonably, and more consideration should be given to reducing energy consumption in the process of optimization.But in the actual distribution, there is more than one type of vehicle, different models also have different loading capacity, different fixed cost, different driving distance and so on.Therefore, the multi-vehicle routing problem considering energy consumption has become the focus of this paper, and also has theoretical and practical significance.Firstly, this paper summarizes the research status of multi-vehicle routing problem at home and abroad, and focuses on the analysis of the components, mathematical model and algorithm of multi-vehicle vehicle routing problem, especially the algorithm to solve multi-model vehicle routing problem.Genetic algorithm (GA) has been chosen in this paper because of its strong robustness, global convergence, ease of operation and less application in multi-vehicle solution.Then combined with the idea of low carbon logistics energy saving and emission reduction, the sum of energy consumption cost and fixed cost related to vehicle type is taken as the optimization goal.The Fleet Size and Mix Vehicle Routing Problem with Energy optimization problem is established and improved genetic algorithm is designed to solve the problem. The feasibility and effectiveness of the algorithm are verified in the benchmark test, and good results are obtained.Finally, the multi-model low-consumption vehicle routing problem is applied to the distribution center of fast moving consumer goods. Due to the characteristics of dense distribution of retail outlets and small but stable demand, the current logistics center adopts a fixed route distribution scheme.In view of this, this paper chooses the urban area as the optimization range from the whole, the result not only reduces the vehicle use, but also improves the service level, is one kind of more reasonable optimization plan.Because of the convenience of model data acquisition and the feasibility and effectiveness of the algorithm, it is a good decision tool for vehicle scheduling and route optimization.The realization of visualization and efficiency of vehicle selection in the algorithm needs to be further discussed. Whether the multi-model low-consumption vehicle path problem model can be applied to the practical problem of solving large-scale customer points still needs further study.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U116

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