Supply Chain Coordination And Collaborative Optimization Of Multi-modal Transport

With the acceleration of manufacturing globalization, the international container multi-modal transport has become an important bridge in the international trade, which is supported by its increasingly globalized transportation service network. In order to provide personalized and integrated service, the multi-modal transport pays more emphasis on cooperation of logistics enterprises and seamless connection of transport modes. The problem of improving the operational efficiency and service quality for supply chain in multi-modal transport has attracted great attention, and become a hotspot in the field of logistics optimization.This dissertation aims to study the above problem through the coordination and collaboration in enterprises, as well as the optimization and scheduling in the logistics terminal. The dissertation includes three research points:(a) the negotiation mechanism and dynamic formation of supply chain in multi-modal transport;(b) decision of transportation speed considering uncertainty and carbon emission; and (c) the impact of resource optimization in logistics terminal on the reliability and on-time delivery of multi-modal transport plan. More specifically, this study can be summarized as follows:Firstly, considering the dynamics, autonomy, and cooperation, a dynamic formation strategy of supply chain for multi-modal transport based on multi-agent system is proposed. The transportation plan is made to meet the demand of consignor through information exchange and negotiation. The formation is divided into bidding decision and winning bidding decision. In bidding decision, the repeated auction mechanism is adopted to create the network of multi-modal transport. To meet the temporal constraint, a price induction mechanism is designed to make carriers reducing their transport time. In winning bidding decision, a Lagrangian-based heuristic algorithm is proposed to obtain the multi-modal transport plan. The simulation experiments show that the formation strategy can provide an effective solution for most of the instances; meanwhile, compared with the mechanism of fixed step size, the autonomous decision can efficiently accelerate the convergence of the negotiation process. Secondly, to deal with the time uncertainty of transport and transit, as well as carbon emission of multi-modal transport, a stochastic model is proposed. Considering the relationship between transport speed and fuel consumption, the activity-based approach is adopted to estimate the carbon emission. The chance constraint is used to describe the satisfaction of time window constraint under uncertainty, and its approximate deterministic equivalent form is obtained to improve the solving speed. To improve the dynamic negotiation of bidding decision in the previous chapter, the network deformation based on alternative set of dynamic transit and node preprocessing with expectation consideration is designed. Considering the nonlinearity of objective function and chance constraint, an improved genetic algorithm based on variable-length chromosome is designed for winning bidding decision. The simulation experiments show that the approximate deterministic equivalent form can efficiently accelerate the convergent speed. Besides, the sensitivity analysis on the confidence level of chance constraint is also conducted and the solution of this model can effectively reduce carbon emission.Lastly, considering the dynamics and uncertainty of vessel arrival time, an integrated scheduling for berth and quay cranes based on robust and reactive policy is proposed. And a model based on multi-agent system under distributed decision is designed. In pre-scheduling stage, using total delay time of vessels as service measure and length of buffer time as robustness measure, the problem is formulated as a robust berth allocation model based on a redundancy policy. And CPLEX is adopted to solve the model. In scheduling stage, for improving the stability of system plan, the as soon as possible strategy and the negotiation mechanism based on contract network protocol are adopted to make full use of berth and quay cranes. The simulation experiments show that CPLEX can solve the optimal solution, and the robust berth allocation plan with real-time scheduling of berth and quay cranes can obviously diminish the effects from uncertainty and improve the stability of system performance.