云环境下的集散型物流服务协同模型与优化

发布时间：2018-04-30 14:21

  本文选题：集散型物流 + 义乌小商品市场　； 参考：《浙江工商大学》2016年博士论文

【摘要】：小商品专业市场在国民经济中有着重要作用,同时,物流产业的发展对于区域经济的发展有显著的促进作用。目前,小商品集散物流服务主要依赖中小物流企业完成,物流组织松散、标准化程度低、信息化水平低、成本高居不下,迫切需要整合物流资源,提高物流运作效率。信息技术有助于促进物流企业内外部的协同,整合物流资源,以应对电子商务等新业态背景下专业市场所面临的更为松散、高效、高质的物流服务需求,提高专业市场集散物流服务能力。云计算作为新一代信息技术的重要代表,为企业提供了一种崭新的信息化建设模式,可加速中小企业的信息化建设进程。本文以云计算为技术基础,以协同管理为理论支撑,针对集散型物流服务构建了物流云服务平台,深入剖析了物流云服务的本质,研究了云环境下集散型物流服务中横向协同与纵向协同模型与优化方法。利用云计算技术的按需定制、按需使用、按需付费的服优势,构建集散型物流云服务平台,促进中小物流企业的信息技术采纳,利用物流云服务平台的IT服务数据与企业IT系统的无缝链接特性,通过物流交易模块实现在线需求和离线需求的统一管理,整合松散物流资源以及集散物流订单进行物流资源的优化配置。本文在文献研究的基础上,首先深入义乌小商品专业市场对其配套物流的供需现状进行调研,总结小商品集散型物流的主要特征为“批量小、平均生命周期短、种类多、需求不可预测性高”。随后,本文根据小商品集散型物流特性提出基于云计算技术的集散型物流服务云平台的建设框架,从云用户的需求出发探讨了云平台的基本软硬件要求、技术架构、服务定制交互流程、传导机理以及集散型物流服务的交易匹配原理,指出实现该物流云平台最关键的技术问题为：①物流资源的虚拟化问题；②云环境下物流企业间的协同管理问题。基于上述研究,本文深入探索了物流服务云平台中的同类物流服务供应商之间的横向和纵向协同模型及优化方法。因船运作为小商品集散物流的主要物流渠道,故本文以物流云平台内的集散型国际船运服务联盟为例,展开研究横向协同模型与优化方法研究。根据协同成员对物流云服务中心的信任程度不同,将平台内的协同成员分为信任型、半信任型两类,在此基础上确定了云服务中心的协同任务和协同资源的整合范围,构建了基于信任的物流资源配置的协同优化模型,并提出运用融合产生式规则的遗传算法求解服务协同网络总体利润最高的匹配方案。然后以小商品专业市场出口交易中相关航线货运服务协同问题为案例,在航线、船容量等约束条件下,从运输服务能力的角度将任务分解、寻优、重组。通过以中东航线的集散型国际海运运输问题为例,对协同模型进行验证、求解,并比较分析了多组试验结果,总结讨论了模型的适用范围及其局限,并提出了模型的改进方向。接着,本文对物流服务云平台中跨类物流服务供应商之间的纵向协同模型及优化方法进行研究。以物流一体化服务组合需求为研究点,基于物流云服务平台的交易环境,提出了基于能力互补的物流服务组合优化方法,旨在从大量的同类异质的物流服务供应商中选择一体化组合方案。本文建立了以物流服务可用性、可靠性和信誉度为约束条件且满足服务费用、服务时间的Web服务组合多目标优化模型,运用改进粒子群多目标优化算法进行求解。研究提出了服务组合参与成员的能力互补度测算方法,通过互补度系数排序优先推荐互补度高服务组合方案,以提高互补度高的企业间进行长期合作的概率,从而促进物流产业的资源整合与协作创新。研究以小商品国际采购物流作为案例,对仓储、包装、集装箱运输、关务等服务节点进行仿真研究,研究结果验证了本文提出方法的有效性。然后,结合前文所述的集散型物流服务平台的功能框架、架构技术和协同管理方法,本文从云发商业模式机理出发研究云物流服务平台运营模式,探索了云平台下的集散型物流服务模式及其增值机制,并总结了云环境下关于集散型物流服务的管理启示。最后,本文总结了论文主要的研究成果以及研究的不足,展望了未来有待解决的研究问题。纵观全文,本文的主要创新点有：①总结了集散型物流云服务的供需特征,构建了基于云计算的集散型物流服务云的架构,有的物流IT云服务与物流交易云服务整合,实现平台内部需求与平台外部需求的协同管理,深入剖析了其软硬件配置、运作机理、协同匹配原理；②在集散型物流服务云环境下,根据协同参与成员对协同中心的信任程度不同,提出物流服务协同成员的信任属性分类方法,并以此建立了基于信任的物流服务协同模型；③在集散型物流服务云环境下,为促进互补度高的物流服务供应商建立长期合作伙伴关系,提出服务组合的服务供应商间的互补度系数的测算办法,并采用互补度降序法推荐组合方案给客户,以提高互补度高的服务组合方案的选择概率,从而促进物流行业资源整合与协同发展；④对现有的智能算法进行改进。提出了基于产生式规则的遗传算法优化算法,缩减了求解范围,加快了求解速度;提出基于网格技术的粒子群多目标优化算法,通过网格粒子密度计算,使帕累托解的尽可能呈现均匀分布。
[Abstract]:The small commodity market plays an important role in the national economy. At the same time, the development of the logistics industry has a significant role in promoting the development of the regional economy. At present, the small commodity distribution logistics service mainly depends on the completion of the small and medium logistics enterprises, the logistics organization is loose, the level of standardization is low, the level of information is low, and the cost is high, and it is urgently needed. Integration of logistics resources to improve the efficiency of logistics operation. Information technology helps to promote the coordination of internal and external logistics enterprises and integrate logistics resources to cope with the more loose, efficient, high-quality logistics service demand in the professional market and the ability to improve the distribution of logistics services in the professional market. As an important representative of information technology, it provides a new model of information construction for enterprises and accelerates the process of information construction of small and medium-sized enterprises. This paper, based on cloud computing as the technical basis, supports the theory of collaborative management, constructs a logistics cloud service platform for distributed logistics services, and deeply analyzes the essence of the logistics service. The model and optimization method of horizontal coordination and vertical coordination in distributed logistics service under the cloud environment are studied. Using the requirements of the cloud computing technology to customize, use and pay for the service, build a distributed logistics cloud service platform, promote the information technology acceptance of the small and medium logistics enterprises, and use the IT service data and enterprises of the logistics cloud service platform. The seamless link characteristics of the IT system, through the logistics transaction module to realize the unified management of online demand and off-line demand, integrate loose logistics resources and distributed logistics orders to optimize the distribution of logistics resources. On the basis of literature research, this paper first penetrates the supply and demand status of Yiwu small commodity specialized market to the supply and demand of its supporting logistics. The main characteristics of small commodity distribution logistics are "small batch, short average life cycle, many kinds and high demand unpredictability". Then, this paper puts forward the construction framework of distributed logistics service cloud platform based on cloud computing technology based on the distribution characteristics of small commodities, and discusses cloud Ping from the demand of cloud users. The basic software and hardware requirements of the platform, the technical architecture, the service customization interaction process, the transmission mechanism and the transaction matching principle of the distributed logistics service, point out that the key technical problems of the logistics cloud platform are: (1) the problem of the virtualization of the logistics resources; (2) the problem of collaborative management between the logistics enterprises under the cloud environment. Based on the above research, In this paper, the horizontal and vertical coordination models and optimization methods of the same kind of logistics service providers in the logistics service cloud platform are deeply explored. As the main logistics channel of the small commodity distribution logistics, this paper takes the distributed international shipping service alliance in the cloud platform as an example to study the horizontal synergy model and the optimization side. According to the different trust degree of the cooperative members to the cloud service center, the cooperative members in the platform are divided into two categories: trust type and semi trust type. On this basis, the cooperative task and the integration scope of the cooperative resources are determined. The cooperative optimization model of the distribution of logistics resources based on trust is constructed, and the transportation is put forward. The genetic algorithm of fusion generation rules is used to solve the matching scheme of the highest overall profit of service cooperative network. Then, with the case of the related airline service synergy in the export trade of the small commodity market, the task is decomposed, optimized and reorganized from the perspective of transportation service capacity under the constraints of route and ship capacity. As an example of the distributed international shipping transportation problem on the east route, the collaborative model is verified, solved, and the results are compared and analyzed. The scope and limitations of the model are summarized and discussed, and the improvement direction of the model is put forward. Then, the longitudinal synergy model among the logistics service providers in the logistics service cloud platform is discussed in this paper. Based on the transaction environment of logistics cloud service platform, the optimization method of logistics service composition based on capacity complementation is proposed, which aims to select an integrated combination scheme from a large number of similar heterogeneous logistics service providers. This paper establishes a logistics service. The multi objective optimization model of Web service combination with the constraints of availability, reliability and reputation as a constraint and service time and service time is solved by the improved multiobjective optimization algorithm of particle swarm optimization. The method of calculating the ability complementarity of the participation members of the service composition is proposed, and the priority of complementarity is recommended by the complementarity coefficient. In order to improve the probability of long-term cooperation among enterprises with high complementarity, it promotes the resource integration and cooperation innovation of the logistics industry. Then, combining the functional framework of the distributed logistics service platform, architecture technology and cooperative management method, this paper studies the operation mode of cloud logistics service platform from the cloud business model mechanism, explores the distributed logistics service mode and its value-added mechanism under the cloud platform, and sums up the distribution and distribution in the cloud environment. In the end, this paper summarizes the main research results and the shortcomings of the research, and looks forward to the research problems to be solved in the future. In the full text, the main innovations of this paper are as follows: (1) the supply and demand characteristics of distributed logistics cloud services are summarized, and the framework of distributed logistics service cloud based on cloud computing is constructed. Structure, some logistics IT cloud services are integrated with logistics trading cloud services to achieve collaborative management of the internal requirements of the platform and the external requirements of the platform. The software and hardware configuration, the operation mechanism and the cooperative matching principle are deeply analyzed. Under the distributed logistics service cloud environment, the trust degree of the Collaborative Reference and members to the cooperative center is different, and the proposed objects are proposed. The trust based trust attribute classification method is used to establish a logistics service coordination model based on trust. 3. In the distributed logistics service cloud environment, a long-term cooperative partnership is established to promote the logistics service providers with high complementarity, and the method of calculating the complementarity coefficient between service providers is proposed. In order to improve the selection probability of the service combination scheme with high complementarity, the combination scheme of complementarity reduction method is recommended to improve the selection probability of the service combination scheme with high complementarity, thus promoting the integration and cooperative development of resources in the logistics industry. To solve the problem, a particle swarm optimization algorithm based on grid technology is proposed. The grid density of particles is calculated to make the Pareto solution as uniform as possible.

【学位授予单位】：浙江工商大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：F259.2
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本文编号：1824899