基于粒子群算法的时间约束顺风车路径问题研究

发布时间：2018-06-04 03:36

本文选题：顺风车 + 时间约束　；参考：《山东大学》2017年硕士论文

【摘要】：随着近年来电子商务的飞速发展,消费者的网购体验越来越好,随之而来的是消费者对线下物流服务的要求也越来越多样化,其中对配送时间的个性化需求就是一个重要方面。面对日益增长的物流市场需求,电商企业及物流企业如何在现有交通基础设施条件下,通过更加合理的资源调配,在实现物流成本节约的基础上不断提高物流服务效率是亟待解决的问题。共享经济的出现为该问题带来了新的解决思路,在互联网共享平台上,供需双方可以通过即时产生劳务关系实现双赢,即双方通过共享物流车辆,配送中心可以通过信息共享平台实时调配自营物流车辆或附近的顾客车辆进行配送服务,其中顾客车辆可以通过共享平台实时接单增加收入,配送中心则可以在一定程度上实现成本节约。基于此,本文提出了一种在互联网共享平台下,既可以满足消费者对物流配送时间个性化需求,又可以通过合理调配顺风车配送来实现物流配送成本有效节约的新型车辆路径问题,即带时间约束的顺风车路径问题(VRPODT)。在这个问题中,配送中心可以自主调度自营配送车辆的同时,还可在共享平台上调配一些愿意为其提供配送服务的顺风车,其被配送中心调配的前提是能够获得一定的酬劳且其目的地与配送目标所在地的距离在其可接受范围之内。本文充分调研了国内外学者对相关问题的研究,梳理了车辆路径问题和粒子群算法的相关理论,分析VRPODT与一般车辆路径问题之间的异同点,针对VRPODT的特性,制定顺风车定价规则和灵活度规则,构建该问题的数学模型,并设计出符合模型约束条件的粒子群算法。为了检验算法的可行性和有效性,本文采用Matlab软件编写算法程序进行实际算例检验,并在相同数据规模和计算环境下,对带时间窗的车辆路径问题(VRPTW)进行求解对比。结果表明:粒子群算法是求解带时间约束的顺风车路径问题的一种有效方法;在合理的顺风车定价规则和灵活度规则下,VRPODT相比VRPTW可有效节省物流成本。本文的研究不仅是对传统VRP模型的拓展和深入,具有较大的理论意义,同时也为企业解决物流资源共享、节约物流成本等问题提供科学决策参考,具有较大的实践意义。
[Abstract]:With the rapid development of electronic commerce in recent years, the online shopping experience of consumers is getting better and better, and the requirements of offline logistics services are becoming more and more diversified, in which the personalized demand for distribution time is an important aspect. In the face of the increasing demand of the logistics market, how can e-commerce enterprises and logistics enterprises allocate more reasonable resources under the existing transportation infrastructure, It is an urgent problem to improve logistics service efficiency on the basis of realizing logistics cost saving. The emergence of sharing economy has brought a new solution to this problem. On the Internet sharing platform, both supply and demand can achieve win-win through the immediate generation of labor relations, that is, both sides can share logistics vehicles. The distribution center can allocate the self-owned logistics vehicle or the nearby customer vehicle to carry on the distribution service in real time through the information sharing platform, in which the customer vehicle can increase the income through the sharing platform real-time receiving the order, Distribution center can realize cost saving to a certain extent. Based on this, this paper puts forward a kind of Internet sharing platform, which can satisfy consumers' personalized demand for logistics distribution time. A new type of vehicle routing problem with time constraint can be realized by reasonably deploying the distribution of the windmill to realize the efficient saving of the cost of the logistics distribution, that is, the problem of the path of the hailing vehicle with time constraints (VRPO DTT). In this problem, distribution centers can independently dispatch their own distribution vehicles, and can also deploy a number of windmills on the shared platform that are willing to provide distribution services for them. It is allocated by the distribution center on the premise that it can get a certain reward and the distance between its destination and the destination of the distribution is within its acceptable range. In this paper, the domestic and foreign scholars' researches on the related problems are fully investigated, and the relevant theories of vehicle routing problem and particle swarm optimization algorithm are combed, the similarities and differences between VRPODT and general vehicle routing problems are analyzed, and the characteristics of VRPODT are analyzed. The pricing rules and flexibility rules of the windmill are formulated, the mathematical model of the problem is constructed, and the particle swarm optimization algorithm is designed to meet the constraints of the model. In order to verify the feasibility and validity of the algorithm, this paper uses Matlab software to program the algorithm for practical example test, and under the same data scale and computing environment, the vehicle routing problem with time window is solved and compared. The results show that the particle swarm optimization algorithm is an effective method to solve the routing problem with time constraint, and that VRPTW can save the logistics cost effectively compared with VRPTW under reasonable pricing rules and flexibility rules. The research in this paper not only extends and deepens the traditional VRP model, but also provides a scientific decision reference for enterprises to solve the problems of logistics resource sharing and logistics cost saving, which is of great practical significance.
【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U492.434

【相似文献】