Cloud Intelligent Logistics Service Selection Based on Combinatorial Optimization Algorithm

Abstract

The selection of intelligent logistics service model has become an important factor in the competition of the entire social logistics industry. Using the technologies such as the Internet of Things (IoT) and cloud computing, the service platform of cloud intelligent logistics (CIL) virtualizes and accesses to the distributed physical logistics resources and logistics capabilities, and relies on its powerful processing and control capabilities to obtain the best service portfolio of CIL. The paper proposes the service combinatorial optimization algorithm (COA). Based on this, it studies the cloud intelligent logistics service and service combination method. The results show that compared with clustering algorithm and differential evolution algorithm, COA algorithm has greater superiority and stability in selection and combination of CIL service; the CIL service has the characteristics of dynamicity and diversity, heterogeneity and distribution, abstraction and similarity; the service portfolio of CIL is divided into three stages: service classification, service negotiation and optimal combination. The application of COA in the CIL selection can greatly reduce the time consumption of combined logistics service and improve the overall service quality of combinatorial service.

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