Study Of Logistics Supply Chain Network Based On Car Following Model In The Traffic Flow

With the rapid development of economy, supply chain has gradually played a dominant role in marketing. Supply chain, a multi-enterprise alliance with various business methods, value orientations, etc, often becomes unstable due to individual behavior of corporations, ultimately affect its overall benefits. Meanwhile, bullwhip effect can also undermine stability. So the study on the stability of the supply chain shows great essential significance.In this thesis, dynamical problems in logistics supply chain are studied through modeling, numerical simulation and theoretical analysis based on car following model in the traffic flow. The influence of multiple downstream stock levels and delivery rate differences on the stability of supply chain, and the effect of next-nearest-neighbor interaction on the stability of supply chain are investigated, as well as for the stability of two kinds of multiple supply chains and the dynamical transition in multiple random supply chains. This thesis consists of the following four main parts:(1) According to the supply chain material conservation model, the supply chain model which consider multiple downstream stock levels and delivery rate differences is proposed. Using the linear stability analysis and nonlinear analysis, the stability conditions is given. Moreover, the mKdV equation is solved and the kink and anti-kink wave solution is obtained. Combining with numerical simulation, the stability of supply chain is discussed in both cases,which consider multiple downstream stock levels and delivery rate differences simultaneously, or multiple downstream stock levels separately. Compared with the one only consider its own stock level, it is found that the consideration of multiple downstream stock levels and delivery rate differences simultaneously, or merely the former, can strengthen the stability of supply chain system. Besides, the system show much better stability when only consider multiple downstream stock levels.(2) Next-nearest-neighbor interaction is introduced into the supply chain and both the linear stability analysis and nonlinear analysis are given. The mKdV equation is solved and the kink and anti-kink wave solution is derived again. Computer simulation results suggest that the next-nearest-neighbor interaction can increase the stability of supply chain, and reduce the bullwhip effect. Furthermore, the greater the next-nearest-neighbor interaction, the more stable the system will be.(3) Two multiple supply chain models are put forward, the supply chain model which consider the overall effect of multiple downstream desired order rate, and the supply chain model which consider the average effect of multiple downstream stock level. Both the linear stability analysis and computer simulation are performed, and the stability conditions and neutral stability line are obtained respectively. It is shown that the two new supply chain models are provided with better stability than the original multiple supply chain model and the bullwhip effect is weakened remarkably. And the more complicated the structure of supply chain model is, the lower the stability will be.(4) Multiple deterministic supply chain model is expanded to multiple random supply chain model, and the dynamical transition of complicated random supply chain network which composed of M parallels and u series machines is studied. Two multiple random supply chain networks are discussed respectively:the production capacity of each machine is random parameters, and the evolution process of delivery rate is affected by white noise. The effect of random parameters (white noise) on multiple supply chain system is investigated through computer simulation, and compared with multiple deterministic supply chain system. It turns out that the random parameters (white noise) reduce the stability of the supply chain system obviously, namely, multiple deterministic supply chain model is more stable than multiple random supply chain model; The more complicated the multiple random supply chain model is, the lower the stability of the system will be; It is found that the system is unstable when the adaptation time is greater than the threshold.Finally, the conclusions of this thesis and the outlook of future researches are presented.