物流配送车辆路径优化方法研究
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摘要
目前,国际物流业正朝着高度专业化和社会化的方向发展。近年来,虽然我国物流业取得了很大的发展,但与国外发达国家相比,仍有较大的差距。在物流各环节中,物流配送对物流企业增加利润起着关键作用,车辆路径问题(VRP)作为解决物流配送问题技术的一部分,得到越来越多研究学者和物流企业的重视。
VRP是一个典型的NP-hard问题,即使在客户规模比较小的情况下,求解也比较困难。因此,研究求解各种条件下VRP的有效算法显得尤为重要。从目前的研究状况来看,虽然对VRP的研究得到了重视,但是仍没有对实际VRP面临的各种情况进行深入的探讨,而且成果比较分散,无论是研究的深度和广度,都不能满足当今物流业迅速发展的需要。
本论文的主要研究内容及创新点如下:
一、设计了求解CVRP的分支切割算法。采用多种切割面,提出新的分支规则、节点选择与删除规则、切割面库更新规则等。通过与国内外算例进行比较,体现了本文提出的算法性能优越性。
二、对多种智能算法在容量约束VRP条件下的性能进行了分析和比较,分析多种算法在处理具体VRP问题时的优、劣势,找出了最适合优化VRP的智能算法。
三、提出了核心路径的概念,并设计了求解CVRP的核心路径禁忌算法。通过对标准数据库进行测试,该算法的优化能力、运算速度和稳定性与同类算法相比具有较大的优势。
四、对各种静态非满载VRP进行比较系统的研究,主要包括:单车场单送货/单集货车辆路径问题;单车场集送一体化车辆路径问题;单车场开放式车辆路径问题;多车场单送货/单集货车辆路径问题;多车场集送一体化车辆路径问题。
五、本文对实时车辆路径问题进行了研究,能应用到当车辆从配送中心出发后,顾客要求突然发生改变后的紧急调度情况,是对更复杂、更接近实际的VRP问题应用的初步探讨。
六、本文提出了物流配送均衡原理,建立了考虑物流配送中心选址的VRP问题的双层规划模型,并设计了优化算法,是对集成物流环境下车辆路径问题的扩展。
七、将能力约束车辆路径问题与自动化仓库拣货问题进行了比较,将研究成果应用到了企业实际当中,具有较大的应用价值。
In recent years, China’s logistics industry has achieved great development, but as compared with foreign developed countries, there are still large gaps. In all the links of logistics, logistics distribution plays a key role in increasing profits of logistics enterprises. As part of solutions to the technical problem of logistics distribution, vehicle routing problem(VRP) is getting more and more attention in academics and enterprises.
VRP is a typical NP-hard problem. Even in the relatively small size of the customers, getting the solution also is difficult. Therefore, studying under all conditions for the effective VRP algorithm appears to be particularly important. Judging from the current situation of the study, although the study on VRP has got much attention, but still not on the actual situation facing the VRP-depth study. The VRP research results are rather scattered, the depth and breadth of which are unable to meet today’s rapid development of the logistics industry.
The textual main work and innovation points include:
Firstly, a branch and cutting algorithm is designed to solve CVRP. The algorithm uses multiple cutting surfaces, the improved branch rules, the nodes selection and deletion rules, the cutting surface updating rules, and so on. Through the comparison of domestic and international examples, the algorithm proposed in the dissertation embodies the performance superiority.
Secondly, the performances of many intelligent algorithms to CVRP are analyzed and compared. These algorithms include genetic algorithm, annealing algorithm, tabu search algorithm. In the dissertation, the advantages and disadvantages of the various algorithms in dealing with the specific issue of the VRP are analyzed, and the most suitable frame of intelligent algorithm is identified for the optimization of VRP.
Thirdly, the concept of core path is proposed in the dissertation. Based on core path, a tabu search algorithm is designed to solve CVRP. The standard database is used to test the ability of the algorithm optimization, computational speed and stability. Compared with the similar algorithms, the algorithm presented in the dissertation has more advantages.
Fourthly, various non-full load VRPs are systematicly studied in the dissertation. These VRP conditions include: single-depot VRP with pick-ups or deliveries; single-depot VRP with with pickups and deliveries; single-depot open VRP; multi-depot VRP with pick-ups or deliveries; multi-depot VRP with pick-ups and deliveries.
Fifthly, the real-time VRP is studied, which can be applied to the situation when vehicles have started from the distribution center and the customer’s requirements suddenly changed. The emergency scheduling problem is the preliminary discussion to the more complex VRP, and it is closer to the actual application.
Sixthly, the logistics distribution equilibrium principle is proposed. The bilevel programming model of VRP problem with logistics distribution center location is presented in the dissertation. Such work is the expansion of VRP in integrated logistics environment.
Seventhly, CVRP and the automated warehouse picking problem are compared. The research results are applied to the actual enterprise and the application achieves good results.
VRP是一个典型的NP-hard问题,即使在客户规模比较小的情况下,求解也比较困难。因此,研究求解各种条件下VRP的有效算法显得尤为重要。从目前的研究状况来看,虽然对VRP的研究得到了重视,但是仍没有对实际VRP面临的各种情况进行深入的探讨,而且成果比较分散,无论是研究的深度和广度,都不能满足当今物流业迅速发展的需要。
本论文的主要研究内容及创新点如下:
一、设计了求解CVRP的分支切割算法。采用多种切割面,提出新的分支规则、节点选择与删除规则、切割面库更新规则等。通过与国内外算例进行比较,体现了本文提出的算法性能优越性。
二、对多种智能算法在容量约束VRP条件下的性能进行了分析和比较,分析多种算法在处理具体VRP问题时的优、劣势,找出了最适合优化VRP的智能算法。
三、提出了核心路径的概念,并设计了求解CVRP的核心路径禁忌算法。通过对标准数据库进行测试,该算法的优化能力、运算速度和稳定性与同类算法相比具有较大的优势。
四、对各种静态非满载VRP进行比较系统的研究,主要包括:单车场单送货/单集货车辆路径问题;单车场集送一体化车辆路径问题;单车场开放式车辆路径问题;多车场单送货/单集货车辆路径问题;多车场集送一体化车辆路径问题。
五、本文对实时车辆路径问题进行了研究,能应用到当车辆从配送中心出发后,顾客要求突然发生改变后的紧急调度情况,是对更复杂、更接近实际的VRP问题应用的初步探讨。
六、本文提出了物流配送均衡原理,建立了考虑物流配送中心选址的VRP问题的双层规划模型,并设计了优化算法,是对集成物流环境下车辆路径问题的扩展。
七、将能力约束车辆路径问题与自动化仓库拣货问题进行了比较,将研究成果应用到了企业实际当中,具有较大的应用价值。
In recent years, China’s logistics industry has achieved great development, but as compared with foreign developed countries, there are still large gaps. In all the links of logistics, logistics distribution plays a key role in increasing profits of logistics enterprises. As part of solutions to the technical problem of logistics distribution, vehicle routing problem(VRP) is getting more and more attention in academics and enterprises.
VRP is a typical NP-hard problem. Even in the relatively small size of the customers, getting the solution also is difficult. Therefore, studying under all conditions for the effective VRP algorithm appears to be particularly important. Judging from the current situation of the study, although the study on VRP has got much attention, but still not on the actual situation facing the VRP-depth study. The VRP research results are rather scattered, the depth and breadth of which are unable to meet today’s rapid development of the logistics industry.
The textual main work and innovation points include:
Firstly, a branch and cutting algorithm is designed to solve CVRP. The algorithm uses multiple cutting surfaces, the improved branch rules, the nodes selection and deletion rules, the cutting surface updating rules, and so on. Through the comparison of domestic and international examples, the algorithm proposed in the dissertation embodies the performance superiority.
Secondly, the performances of many intelligent algorithms to CVRP are analyzed and compared. These algorithms include genetic algorithm, annealing algorithm, tabu search algorithm. In the dissertation, the advantages and disadvantages of the various algorithms in dealing with the specific issue of the VRP are analyzed, and the most suitable frame of intelligent algorithm is identified for the optimization of VRP.
Thirdly, the concept of core path is proposed in the dissertation. Based on core path, a tabu search algorithm is designed to solve CVRP. The standard database is used to test the ability of the algorithm optimization, computational speed and stability. Compared with the similar algorithms, the algorithm presented in the dissertation has more advantages.
Fourthly, various non-full load VRPs are systematicly studied in the dissertation. These VRP conditions include: single-depot VRP with pick-ups or deliveries; single-depot VRP with with pickups and deliveries; single-depot open VRP; multi-depot VRP with pick-ups or deliveries; multi-depot VRP with pick-ups and deliveries.
Fifthly, the real-time VRP is studied, which can be applied to the situation when vehicles have started from the distribution center and the customer’s requirements suddenly changed. The emergency scheduling problem is the preliminary discussion to the more complex VRP, and it is closer to the actual application.
Sixthly, the logistics distribution equilibrium principle is proposed. The bilevel programming model of VRP problem with logistics distribution center location is presented in the dissertation. Such work is the expansion of VRP in integrated logistics environment.
Seventhly, CVRP and the automated warehouse picking problem are compared. The research results are applied to the actual enterprise and the application achieves good results.
引文
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