基于时间约束下物流企业运输成本优化研究

发布时间：2018-05-27 07:40

本文选题：物流企业 + 运输成本　；参考：《华北电力大学》2014年硕士论文

【摘要】：随着科学技术的发展,通过提高产品性能和劳动生产率来提高企业的利润变得越来越困难。在追求最大利润目标的驱动下,人们发现物流占企业成本的较大比例,而通过优化供应链的某一环节可以大大降低物流成本。为了在竞争日益激烈的商品市场上获得优势,企业对物流的优化研究迅速发展起来。本文通过对物流企业的物流成本组成部分进行分析发现：物流企业运输成本占企业总成本很大比例。因此对物流企业运输成本优化问题研究具有较强的理论价值和现实意义。物流企业的运输成本不仅与车辆运输过程中发生的固定成本和变动成本有关,而且运输时间的时间窗约束也会影响到运输成本。物流企业根据客户提出的时间窗约束支付相应的惩罚费用,从而引起运输成本的增加。时间窗可以分成软时间窗、硬时间窗和混合时间窗三种。在实际的运输过程中客户对运输时间的要求一般都是弹性的,因此本文选取软时间窗为研究对象。但是,现有关于时间窗运输成本优化研究的文献中忽略了一种现象：车辆在运输过程中由于路况或人为因素会发生运输中断,从而造成运输时间延长,即时间转换约束。由于忽略了时间转换约束的影响,进而造成了物流企业决策者对运输时间预测的误差。因此,对考虑时间转换约束运输成本模型的研究能够更好地反映实际运输过程。本文针对现有文献中关于考虑时间窗约束的运输成本模型研究的难点和不足,首先从时间窗的分类进行分析,确定不同时间窗的适用范围。然后,将项目网络研究中的时间转换约束引入运输问题。针对这一问题,本文在所建立的考虑时间窗约束下运输成本模型基础上,加入了时间转换约束。通过对两个模型的分析发现,时间转换约束对物流企业运输成本的影响不容忽视。在建模的过程中考虑到物流企业车辆数也是影响其运输成本的重要因素,因此本文以运输成本最小和物流企业自有车辆最小作为模型的两个目标,进而构建了两个双目标模型,并设计了改进的遗传算法来求解该双目标非线性问题。最后,通过S物流企业某次运输过程验证该算法的可行性和有效性。在上述研究的基础上,本文进一步研究了时间转换约束对物流企业运输成本产生的影响。通过实例测试发现：(1)由于时间转换约束的影响,实际运输过程中产生的成本要高于以往传统运输成本模型下的计算结果；(2)时间转换约束改变了物流企业的最优运输路径。因此,在运输成本优化问题中考虑时间转换约束的影响对物流企业有效管理有重要意义。
[Abstract]:With the development of science and technology, it is more and more difficult to improve the profit of enterprises by improving the product performance and labor productivity. Driven by the pursuit of the goal of maximum profit, it is found that logistics accounts for a large proportion of the cost of the enterprise, and logistics costs can be greatly reduced by optimizing a certain part of the supply chain. In order to gain advantage in the increasingly competitive commodity market, the research on logistics optimization has developed rapidly. By analyzing the logistics cost components of logistics enterprises, it is found that the transportation cost of logistics enterprises accounts for a large proportion of the total cost of enterprises. Therefore, the research on logistics enterprise transportation cost optimization has strong theoretical value and practical significance. The transportation cost of logistics enterprise is not only related to the fixed cost and variable cost in the course of vehicle transportation, but also the time window constraint of transportation time will affect the transportation cost. The logistics enterprises pay the penalty according to the time window proposed by the customer, which results in the increase of the transportation cost. Time window can be divided into soft time window, hard time window and mixed time window. In the actual transportation process, the customer's request for transportation time is generally elastic, so the soft time window is chosen as the research object in this paper. However, a phenomenon has been neglected in the literature on the optimization of transportation cost in time windows: the transportation interruption may occur in the course of vehicle transportation due to road conditions or human factors, which results in the prolongation of transportation time, that is, the constraint of time conversion. Because of neglecting the influence of time conversion constraint, the decision maker of logistics enterprise makes the error of transportation time prediction. Therefore, the research on the transport cost model with time conversion constraints can better reflect the actual transportation process. Aiming at the difficulties and shortcomings of the research on transportation cost model with time window constraints in the existing literature, this paper first analyzes the classification of time windows and determines the applicable scope of different time windows. Then, the time conversion constraints in the project network research are introduced into the transport problem. In order to solve this problem, the time conversion constraint is added to the transport cost model considering the time window constraint. Through the analysis of the two models, it is found that the influence of time conversion constraints on transportation cost of logistics enterprises can not be ignored. In the process of modeling, it is considered that the number of vehicles in logistics enterprises is also an important factor affecting their transportation cost. Therefore, this paper takes the minimum of transportation cost and the minimum of owned vehicles of logistics enterprises as the two objectives of the model, and then constructs two double-objective models. An improved genetic algorithm is designed to solve the two-objective nonlinear problem. Finally, the feasibility and effectiveness of the algorithm are verified by a transportation process in S logistics enterprise. On the basis of the above research, this paper further studies the influence of time conversion constraints on transportation costs of logistics enterprises. It is found that the cost in the actual transportation process is higher than that in the traditional transportation cost model because of the influence of the time conversion constraint) the time conversion constraint changes the optimal transportation path of the logistics enterprise. Therefore, it is important for logistics enterprises to consider the influence of time conversion constraints in transportation cost optimization.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F253.7;F259.23

【参考文献】