基于物联网的集配中心MiIk Run物流实时车辆调度系统研究

发布时间：2018-02-25 03:33

本文关键词： 物联网集配中心 Milk Run 车辆调度遗传算法　出处：《广东工业大学》2014年硕士论文　论文类型：学位论文

【摘要】：工业园区是多企业集聚而成,以资源及服务共享为特点的产业集群。其中,由工业园区集配中心(Supply Hub in Industrial Park, SHIP)以Milk Run物流模式面向园区多企业提供的公共仓库及公共车队物流服务是第三方物流运营商为缓解园区土地、车辆运输等资源压力提出的一种集成化公共物流运作模式。Milk Run物流是用同一货运车辆到园区多企业进行循环取配货的操作模式。其高频次、小批量、准时性的运作特点使得车辆调度过程中需综合考虑循环次序、运输批量、到达时间窗及园区各企业的实时生产数据等动态因素。因此,传统的静态车辆调度已无法满足SHIP公共物流的实时性、敏捷性及高效性的要求。而物联网技术作为当代物流配送系统的新兴技术可实现在物流运作过程中对车辆及货物进行实时跟踪管理,动态采集各物流节点实时数据,使得SHIP能依据物流资源的实时状态合理优化车辆调度。以提高Milk Run物流运输灵活性,合理配置及规划物流资源,降低园区物流总成本。因此,本文借鉴已有研究成果,依托物联网技术,研究SHIP面向多企业提供Milk Run物流服务的实时车辆调度优化问题。研究内容主要包括以下几个方面： (1)探讨了产业集群模式下的工业园区公共物流体系及其车辆调度问题,提出了一种基于物联网的小批量、高频率、准时制的Milk Run物流运作模式； (2)分析了SHIP车辆调度所存在的问题,提出了SHIP基于物联网的Milk Run物流实时车辆调度基本框架,实现基于物联网技术的实时数据采集与管理,调度实时任务,达到实时车辆调度分工与协作的目的； (3)针对SHIP中Milk Run取配货车辆路径问题,建立了Milk Run公共物流多车型实时车辆调度的数学模型,并在遗传算法的基础上,改变染色体编码方式,采用局部竞争选择策略方式,提出基于多车型分配的改进遗传算法； (4)在实时车辆调度框架的基础上,采用C#语言实现了一种基于物联网技术实时车辆调度系统,通过运行实例,全面展示了系统功能。本文所研究的问题具有理论价值和实际意义,主要表现在：其一,从理论上研究了面向SHIP的Milk Run物流运作模式,实现物联网技术在SHIP实时车辆调度全程一体化应用,可为类似工业园区信息平台建设提供参考；其二,建立了基于物联网的MilkRun公共物流实时车辆调度数学模型,设计其相应的智能改进遗传算法,为决策提供支持。
[Abstract]:Industrial parks are industrial clusters characterized by the sharing of resources and services. By supply Hub in Industrial Park (SHIPP), the public warehouse and public fleet logistics service provided by the Milk Run logistics model to many enterprises in the park is the third party logistics operator to alleviate the land of the park. Milk Run Logistics is an operation mode of recycling goods from the same freight vehicle to many enterprises in the park. The operational characteristics of punctuality make it necessary to take into account the dynamic factors such as cycle order, transportation batch, arrival time window and real-time production data of the enterprises in the park. Traditional static vehicle scheduling can not meet the real-time performance of SHIP public logistics. As a new technology of modern logistics distribution system, Internet of things technology can realize real-time tracking and management of vehicles and goods in the process of logistics operation, and dynamically collect real-time data of each logistics node. In order to improve the flexibility of Milk Run logistics transportation, reasonably configure and plan logistics resources, and reduce the total logistics cost of the park, SHIP can optimize the vehicle scheduling reasonably according to the real time state of logistics resources. Therefore, based on the existing research results and the Internet of things technology, this paper studies the real-time vehicle scheduling optimization problem of SHIP to provide Milk Run logistics services for multi-enterprises. The research contents mainly include the following aspects:. 1) this paper discusses the public logistics system of industrial park and its vehicle scheduling problem under the industrial cluster mode, and puts forward a small batch, high frequency and punctual Milk Run logistics mode based on the Internet of things. This paper analyzes the problems existing in SHIP vehicle scheduling, puts forward the basic framework of Milk Run logistics real-time vehicle scheduling based on Internet of things in SHIP, realizes the real-time data acquisition and management based on the Internet of things, and schedules real-time tasks. To achieve the goal of real-time vehicle scheduling division and cooperation; 3) aiming at the routing problem of Milk Run in SHIP, the mathematical model of real-time vehicle scheduling for Milk Run public logistics is established. Based on genetic algorithm, the chromosome coding method is changed and the local competitive selection strategy is adopted. An improved genetic algorithm based on multi-vehicle assignment is proposed. Based on the real-time vehicle scheduling framework, a real-time vehicle scheduling system based on the Internet of things technology is implemented by using C # language. The system functions are demonstrated by a running example. The problems studied in this paper are of theoretical value and practical significance. Firstly, the SHIP oriented Milk Run logistics operation mode is theoretically studied, and the integration of Internet of things technology in SHIP real-time vehicle scheduling is realized. It can provide reference for the construction of information platform in similar industrial parks. Secondly, the mathematical model of real-time vehicle scheduling for MilkRun public logistics based on the Internet of things is established, and the corresponding intelligent improved genetic algorithm is designed to provide support for decision making.
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TB497

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