汽车零部件双向物流路径优化模型及仿真研究

发布时间：2018-10-17 13:29

【摘要】：近年来,伴随着汽车销量及净利润下滑,汽车生产厂商追求效益、降低成本的压力必然向汽车产业链的物流环节释放。而汽车零部件供应物流和回收物流作为汽车产业链优化中最为关键的一环,一直是国内外专家研究的热点。然而,长期以来我国零部件供应物流及次品回收物流是分离的,往往会出现多种物流业务平行开展,物流环节重复,资源配置浪费的现象,严重制约汽车行业的健康发展。所以,本文探讨在原有供应物流网络基础上扩展回收物流模块,将双向物流的思想引入汽车零部件物流中。本文在归纳总结国内外成熟汽车零部件物流模式的基础上,对比分析现有供应物流和回收物流的优缺点,指出双向物流模式是汽车零部件物流发展的新方向。同时详细介绍了汽车零部件采购物流及回收物流路径优化的基本模型,通过对原有供应物流路径优化模型的优化再设计,指出实现双向物流的关键在于取货路径的安排调度。尤其是一个科学合理的路径优化方案能够有效地控制小批量、多批次物流的成本。对此,本文将汽车零部件双向物流路径优化模型抽象为带软时间窗的同时取送货路径优化模型即VPRSPDTW模型。相比传统的路径优化模型,该模型增加了同时取送货需求限制和时间窗约束,使之更加贴近实际应用。在模型求解上,结合遗传算法、禁忌算法、模拟退火算法的优点,设计了适合VRPSPDTW模型的混合遗传禁忌模拟退火算法。通过对算例进行求解,从以下两个方面进行对比分析:其一,通过与禁忌算法与模拟退火算法的对比,分析不同算法策略下优化效果及性能,指出在使用车辆数、配送距离优化方面,混合遗传禁忌模拟退火算法较禁忌算法、模拟退火算法具有明显优势;其二,不同物流策略下,对单向物流与双向物流的优化效果对比,指出双向物流模式在降低物流成本,提高物流资源利用率上效果卓著,验证了算法及模型的有效性及科学性。
[Abstract]:In recent years, with the decline of automobile sales and net profit, the pressure of automobile manufacturers to pursue efficiency and reduce costs is bound to release to the logistics link of automobile industry chain. As the most important part in the optimization of automobile industry chain, the logistics of auto parts supply and recovery has always been the hot spot of domestic and foreign experts. However, for a long time, parts supply logistics and defective product recovery logistics in China have been separated, which often lead to the parallel development of various logistics services, duplication of logistics links and waste of resources allocation, which seriously restrict the healthy development of the automobile industry. Therefore, this paper discusses the expansion of recovery logistics module on the basis of the original supply logistics network, and introduces the idea of two-way logistics into automobile parts logistics. On the basis of summing up the domestic and foreign mature automobile parts logistics models, this paper compares and analyzes the advantages and disadvantages of the existing supply logistics and recovery logistics, and points out that the two-way logistics model is the new direction of automobile parts logistics development. At the same time, the paper introduces the basic model of automobile parts purchasing logistics and recovery logistics route optimization in detail. Through the optimization and redesign of the original supply logistics route optimization model, the key to realize the two-way logistics is the arrangement and scheduling of the pick-up route. In particular, a scientific and reasonable path optimization scheme can effectively control the cost of small batch and multi-batch logistics. In this paper, the two-way logistics path optimization model of automobile parts is abstracted as VPRSPDTW model with soft time window. Compared with the traditional path optimization model, this model adds both delivery requirement constraints and time window constraints to make it more close to practical application. Based on the advantages of genetic algorithm, Tabu algorithm and simulated annealing algorithm, a hybrid genetic Tabu simulated annealing algorithm suitable for VRPSPDTW model is designed. By solving an example, the following two aspects are compared and analyzed: first, by comparing with Tabu algorithm and simulated annealing algorithm, the optimization effect and performance under different algorithm strategies are analyzed, and the number of vehicles in use is pointed out. In distribution distance optimization, hybrid genetic Tabu simulated annealing algorithm has obvious advantages over Tabu algorithm and simulated annealing algorithm. Secondly, under different logistics strategies, the optimization effects of unidirectional logistics and two-way logistics are compared. It is pointed out that the bi-directional logistics model is effective in reducing the logistics cost and improving the utilization ratio of logistics resources, which verifies the validity and scientific nature of the algorithm and model.
【学位授予单位】：杭州电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F426.471;F252

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