Research On Supplier Selection And Optimization Problems In Logistics Service Supply Chain

With further development of the social division of labor, service outsourcing has become a new trend, and service supply chain (SSC) attracts more and more attention after product supply chain. As an important branch of SSC, logistics service supply chain (LSSC) is one of the hot points in the field of logistics research and logistics industry. It provides a good way for logistics service integrator who is the core enterprise in LSSC to integrate the service resources, provide customized and full-range of logistics services.Although LSSC has attained much attention, its research has barely begun, many sixty-four-dollar questions have not solved. As a core member of LSSC, the logistics service integrator plays a leading role in the design and operation. In this paper, we propose some methods, which are based on the theories of fuzzy mathematics, logistics management and date mining technology to analyze the optimizing and selecting processes of the functional logistics service provider (FLSP). The main contents and key aehievements are as follows:After coordinating the domestic and abroad literature review, some basic theory such as the structure and essence of LSSC is discussed in this paper. Then we analyze the design principle and processes of LSSC, which mainly including logistics services requirements analysis, logistics services type analysis, the supply chain structure design, member selection as well as operation and evaluation. Furthermore, some key problem of supplier selection and operation are contacted with the designing and operating process of LSSC, and then we give the main content of supplier management in LSSC.As a key part of the construction of LSSC, the functional logistics service provider (FLSP) partner selection is discussed firstly. Considerating the E-commerce environment and logistics service characteristic, the paper gives a service supplier selection framework which contains service quality, service prices, service capacity and cooperation risk as second-level indicators. Considering the uncertainty of decision environment, the interval DEA (date envelopment analysis) model is proposed to evaluate and select the FLSP partner. We also propresed the solution of interval DEA based on the possibility degree to ranking the DMUs, which can combine subjective idea of decision-maker with objective evaluate of DEA.In the operating process of LSSC, the task allocation model based on single logistics capacity and multiplicate logistics capacities are discussed. The basic flow of task allocation is given firstly. Based on multi-objective mixed integer programming theory, the decision model jointly considers service price, service quality and satisfying degree in service revenue discount environments. An asymmetric fuzzy-decision making technique is applied to enable the decision-maker to assign different weights to various criteria. Numerical example shows the infection of decision preference, service revenue discount and other correlation factors.Data mining technology is discussed for supplier management solution in LSSC, and a new fuzzy clustering algorithm based on AFS theory is applied for logistics supplier classification. We establish a new topology space for the clustering problems, and a new distance based on neighbors in the topology space is proposed. In the clustering algorithm, the Euclidean metric is replaced by the new distance based on the order relationship of the samples on the attributes. As a result, using the method to Iris data we show it has a better result and clearer classification than the other clustering algorithms. This study shows that the AFS topology fuzzy clustering algorithm can obtain an high clustering accuracy according to order relationship. Finally an application example for logistics supplier classification has been given for testing the feasibility and effectiveness of the proposed method.