三维货物配载与车辆路径问题研究

发布时间：2018-01-19 20:33

本文关键词： 三维配载多车型车辆路径组合优化　出处：《华南理工大学》2015年硕士论文　论文类型：学位论文

【摘要】：配送活动是根据客户的要求,对货物进行拣选、加工、组配等作业,并送达指定地点的物流活动,货物的配载与配送过程是配送活动的主要活动之一,其成本也是配送活动中的主要成本之一,通过提高车辆的配载效率、优化车辆的配送路径,可以有效降低运输配送成本,节省企业的物流运作成本,提高企业的利润率。目前货物配载多以考虑体积和重量为主,在实际的货物配载中忽略了货物的不同规格尺寸对配载的影响,容易造成在实际配载时出现体积和重量都满足车辆额定容积和载重的约束,但受到货物的规格尺寸限制而无法完全配载的情况;货物配载与车辆的配送路径的研究主要以分开研究为主,将两者结合从整体考虑的研究较少,本文的研究将货物配载和车辆路径问题结合起来研究三维货物配载与车辆路径组合的优化模型,以车辆容积利用率、载重利用率及配送成本为优化目标,优化货物配载与车辆路径。本文将三维、多车型的配载与车辆配送路径相结合,考虑货物尺寸、车辆尺寸、多车型、车辆重心等约束问题建立以配送成本最低、车辆容积利用率最高、车辆载重利用率最高为优化目标的组合优化模型。在建立模型的基础上,为解决三维、多车型的货物配载,设计剩余空间合并策略、配载优化算法、配载检验算法用于实现货物的配载;选择遗传算法作为优化算法,设计染色体编码、种群初始化算法,确定选择、交叉、变异操作规则,提高算法的适应性、降低早熟的可能性同时加快算法的收敛速度,将配载相关算法和遗传算法相结合,实现模型的求解。为了验证本文算法的求解效果,利用Gendreau等人提出的标杆问题讨论算法的参数设置及算法求解的有效性,并将本文算法求解结果与Gendreau等人的结果进行对比分析,验证了本文求解算法的有效性;最后以某知名物流企业的实际业务数据作为案例,采集该企业的客户需求信息、位置信息等数据,利用本文求解算法进行求解,并与原方案进行对比分析,验证了本文模型算法在实际应用问题上具有较好的求解效果。
[Abstract]:Distribution activity is to select, process, group and deliver goods to designated places according to the requirements of customers. The loading and distribution process of goods is one of the main activities of distribution activities. Its cost is also one of the main costs in distribution activities. By improving the efficiency of vehicle stowage and optimizing the distribution path of vehicles, the cost of transportation and distribution can be effectively reduced, and the logistics operation costs of enterprises can be saved. To improve the profit margin of the enterprise. At present, the bulk and weight of the cargo are mainly considered in the stowage, and the influence of the different size of the goods on the stowage is neglected in the actual loading. It is easy to cause the restriction of the volume and weight of the vehicle to meet the rated volume and load when the actual load is loaded, but it is unable to be completely loaded because of the restriction of the size of the cargo. The research on the distribution route of cargo stowage and vehicle is mainly focused on the separate research, and the research on the combination of the two from the overall consideration is less. The research of this paper combines the problem of cargo stowage and vehicle routing to study the optimization model of the combination of cargo stowage and vehicle routing, with the vehicle volume utilization ratio, load utilization ratio and distribution cost as the optimization goal. This paper combines the three dimensional and multi-model stowage with the vehicle distribution path, considering the size of goods, vehicle size, multi-model, vehicle center of gravity and other constraints to establish the lowest delivery cost. The combined optimization model with the highest utilization ratio of vehicle volume and the highest utilization rate of vehicle load is the optimal model. On the basis of the model, the combined strategy of remaining space is designed to solve the cargo stowage of three-dimensional and multi-vehicle models. The stowage optimization algorithm and the stowage inspection algorithm are used to realize the stowage of the goods. Genetic algorithm is selected as the optimization algorithm, chromosome coding, population initialization algorithm, selection, crossover, mutation operation rules, improve the adaptability of the algorithm. To reduce the possibility of premature convergence and speed up the convergence of the algorithm, the load correlation algorithm and genetic algorithm are combined to achieve the solution of the model, in order to verify the effectiveness of the algorithm in this paper. The parameter setting of the algorithm and the validity of the algorithm are discussed by using the benchmarking problem proposed by Gendreau et al. The results of this paper are compared with those of Gendreau et al. The validity of the algorithm is verified. Finally, take the actual business data of a well-known logistics enterprise as a case, collect the customer demand information, location information and other data of the enterprise, use this algorithm to solve, and compare with the original scheme. It is verified that the model algorithm is effective in practical application.
【学位授予单位】：华南理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U492

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