To deal with the complex structure and difficulty in precise expression of the interaction between entities in the steel production logistics system, this paper uses complex network theory and multiagent system engineering to simulate the complex steel production logistics system, and thereby calculate related parameters, gather statistics, and optimize the steel production logistics system. According to the analysis, the processing of logistics is low in efficiency because 19 pieces of equipment are involved from the beginning of the logistics subject processing to the final formation of steel, while only a few processes are required for about half of the auxiliary material or auxiliary process. The system logistics is not compact because most of the equipment used in steel production has only a single function and a limited service area, whereas a higher degree distribution indicates a higher importance in a piece of equipment in the network. This is a must to guarantee the normal operation of the equipment with a higher degree distribution. The simulation results are basically the same with the actual production results, and the error is within the acceptable range, which proves that the simulation system is correct and effective.
Service-oriented manufacturing is the new development of manufacturing systems, and manufacturing supply chain service is also an important part of the service-oriented manufacturing systems; hence, the optimal selection of parts suppliers becomes one of key problems in the supply chain system. Complex network theories made a rapid progress in recent years, but the classical models such as BA model and WS model can not resolve the widespread problems of manufacturing supply chain, such as the repeated attachment of edge and fixed number of vertices, but edges increased with preferential connectivity, and flexible edges’ probability. A core model is proposed to resolve the problem in the paper: it maps the parts supply relationship as a repeatable core; a vertex’s probability distribution function integrating the edge’s rate and vertex’s degree is put forward; some simulations, such as the growth of core, the degree distribution characteristics, and the impacting of parameter, are carried out in our experiments, and the case study is set also. The paper proposed a novel model to analyze the manufacturing supply chain system from the insights of complex network.
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