Small And Distributed Logistics Service Collaboration In Cloud Computing Environment

Specialized small commodity market accounts for a considerable proportion of the national economy. Meanwhile, the development of logistics industry has significant effects on promoting regional economy growth. Currently a great deal of small and distributed logistics services are provided by Small and Medium-sized Enterprises (SMEs), which are loosely organized and are still on the initial stage of the informatization level. Besides, the overall level of logistics services remains low; it is urgent to improve logistics management level through information technology such as cloud computing, so as to integrate logistics services, decrease logistics operating costs, increase revenues, improve service quality and so on. This paper focuses on the problem of collaboration among small and medium logistics service providers; using cloud computing as technology base and collaborative management as theory base, studies the nature and method of cloud logistics.On the basis of literature research, firstly, DWV3 classification is used in this paper to investigate the current situation of logistics services, which support the transactions of small commodities market in Yiwu. The logistics service characteristics obtained from the study are small-volume, short life cycle, high variety and high unpredictable variability, coming up with the suggestions of adopting cloud computing technology to upgrade logistics system. Next, the frame of logistics service cloud platform is set based on the characteristics and the technical architecture of logistics service cloud is then proposed which includes two modules. One of the module provides both hardware IT devices and software IT application services. Owing to the module’s advantages of on-demand pricing, dynamic on-demand configuration and timely upgrade, the incentive of adopting logistics cloud is largely generated, especially for small and medium logistics service providers. As a result, the level information of logistics industry can be promoted. The other module is the logistics service trade center. Aims at forming collaborative working environment, the logistics resources can be managed in centralized logistics service cloud. Each logistics services provider can set the availability attribution of resources, which can lead to unify management of online demand and offline demand. A seamless connection between the logistics service cloud and its users must be provided to support the implementation of the architecture.Then, horizontal collaboration among logistics service providers with homogeneous services in logistics service cloud platform is studied. Small commodity export shipping services problem is taken as a case to carry out the research. Since usually the shippers own only a small quantity of goods in small commodity shipping, the difference between actual demand and estimated demand may be significant in commodity export shipping services. Therefore, it is meaningful to increase the overall load rate to deal with the difference. A trust based collaboration model is introduced for relative routes with two types of participations who are trust partners and semi-trust partners. Then a production-rule-based genetic algorithm is proposed to match transport tasks and service capabilities with the constraints of ship capacity and routing order from the angle of shipping service capability. The idea of segmenting the demand into small pieces of a carrier and then allocating the recombined tasks to members in collaboration is used in the algorithm. The Mid-East routing shipping services are taken as an example to verify the effectiveness of the models. The maximum overall profit of the collaboration exists in the model when each partner is trust partner.Finally, vertical collaboration among logistics service providers with heterogeneous services in logistics service cloud platform is studied. Based on the ontology study of logistics QoS (Quality of services) requirements and logistics resources, a dynamic logistics Web service composition model among logistics service provider is constructed. Then improved particle swarm optimization (PSO) algorithm with grid technology is used to solve the multi-objective problem, in which a parameter of complementary degree is introduced. A set of Pareto with a number of optimized solutions can be obtained with the algorithm, then the complementary degree of each solution can be calculated. The solutions for selection are shown to customers according to the sequence of complementary degree from high to low, so the probability of logistics service providers with high complementary degree can be increased. Small commodity international procurement logistics in Yiwu is taken as an example to carry out the simulation of Web service composition, with the services nodes of warehousing, packaging, container transportation, declaration. The results demonstrate that the proposed model is efficient and promising.In the end, this paper explores small and distributed logistics service mode based on logistics cloud computing platform and summarizes paper’s main research results and the lack of research, prospects the future research questions remaining to be solved.