Research On Robustness Of Double-layer Supply Chain Networks Considering Logistics And Capital Flows

With the development of social productive forces,the market competition becomes more and more fierce,and the main body of competition gradually becomes the supply chain.For managers,improving the viability of the supply chain when facing risks is the premise for them to consider other issues.In the past,supply chain research based on complex network theory divided supply chain network into logistics network,capital network and information flow network according to different research objectives,and studied them separately.However,the theory of supply chain management holds that the supply chain is composed of three elements:capital flow,information flow and logistics,which depend on each other and influence each other to maintain the normal functions of the supply chain system.There is a conflict between the previous research and the theory of supply chain management,that is,if one element is studied independently in the interdependent system without considering the influence of the other two.It may lead to biases in the research result.Based on this problem,this thesis makes a series of research:Firstly,it innovatively constructs a two-layer supply chain network model based on multi-layer network model,taking logistics network and capital flow network as examples by considering the coordination and correspondence between them in the process of supply chain operation.The network model of interdependent network model of capital network and logistics network is constructed,and the supply chain system is studied from a more systematic and complete point of view.This thesis probes into the differences between the traditional single-layer logistics network model and the network model based on the interdependence of capital network and logistics network.Then,according to the property that the similarity between layers of multi-layer networks affects the robustness of the whole network,a robust optimization method of multi-layer supply chain networks based on edge removal is proposed.The simulation experiment shows that there is a critical point in the method of removing edges to improve the robustness of the system,and the effect of ascending removal is much better than descending removal.Finally,in order to improve the efficiency of the use of resources,the robustness optimization problem is transformed into a classic knapsack problem in operational research,and genetic algorithm is used to maximize the robustness of the supply chain system with minimum cost.The results show that compared with the simple sequential removal,the use of genetic algorithm not only improves the utilization efficiency of resources,achieves a better optimization effect with fewer resources,but also raises the upper limit of the optimization strategy.Based on the supply chain management theory,complex network theory and heuristic algorithm,this thesis studies the influence of the subsystem composed of supply chain elements on the whole supply chain system,and quantitatively analyzes the influence.We found that the conclusion of considering the two elements at the same time is different from the previous research.In theory,this thesis considers the interaction between capital flow and logistics in the supply chain,constructs a new multi-tier supply chain network model,enriches the research in this field,and according to the relevant research of multi-layer network theory,an innovative network robustness optimization strategy based on edge removal is proposed.In practice,according to the research results,this paper gives the management enlightenment:managers can improve the resilience of the supply chain significantly by reducing the loans of small and medium-sized enterprises in the supply chain,at the cost of reducing the extra income of the supply chain.This has a certain guiding significance for the actual supply chain operation.