Computational Techniques Of Multimodal Service Network Capacity For Express Shipment

As the key research topic of multimodal transportation system, structure and shipping capacity of express shipment service network have attached many attentions of both the mangers and the researchers of the multimodal commodity transportation. For the reason that there are no systematic researches on the shipping capacity of multimodal service network for express shipment under the idea of "express shipment", this thesis works on the computational techniques of multimodal service network capacity for express shipment. The main work includes the following interrelate parts:1. Along with the trend of multimodal express shipment, current situation as well as the necessity of computing capacity of multimodal service network for express shipment are reviewed and depicted.2. Concepts and classifies of multimodal service network for express shipment are proposed. Based on them, detail concepts as well as the constitution of the multimodal service network capacity for express shipment are put forward, including the analysis of the impact factor and simple measures of the service network capacity.3. Computational technique of multimodal long-haul service network capacity for express shipment is analyzed. Topology representation and transshipment link in hub point of multimodal long-haul service network for express shipment are put forward firstly. Then, with OD matrix estimation method in Traffic Engineering, the multimodal long-haul service network capacity matrix is determined. During that, the Maximum Likelihood Estimation on the difference between the container flow and its carrying capacity on the key service link are used to determine the increase factor of express shipment matrix which is used to calculate the capacity matrix. A numerical case is used to verify the proposed mathematical model and the solution algorithm.4. Computational technique of multimodal regional service network capacity for express shipment is analyzed. Topology representation of multimodal time-defined regional service network for express shipment is given out. In this process, the concepts, i.e. the physical route and the time-space path on multimodal time-defined regional service network are addressed. Based on the concepts of physical route and time-space path, a "two stages labeling" algorithm is proposed to search the K shortest time-space path between an OD pair. As the K shortest time-space path algorithm has been proposed, the computational method of multimodal time-defined regional service network capacity for express shipment is formulated as well. A numerical case is used to verify the proposed model and the solution algorithm.5. Computational techniques of multimodal service network capacity for express shipments with various decision individuals are studied. For policy constituter of commodity shipment, the maximal effective capacity and potential capacity of multimodal service network for express shipments versus different defined delivery time are determined; for the shipper and the carrier, standing on the point that the shippers choosing the carriers, while the carriers making up their own shipping strategies, the mathematical models for economic capacity of multimodal service network for express shipments are formulated, these two models are integrated with a bi-level programming. The upper programming cares about the process of the shippers' choosing the carriers. On the other hand, the lower programming is the express shipment flow assignment model on the physical routes of the carriers and the logistics service provider (LSP). A numerical case is used to verify the proposed mathematical model and the solution algorithm.6. Computational technique of multimodal service network capacity for express shipments with reliability constraints of defined delivery time is researched. For the reason that during the commodity shipping process, the running time on service link of carrying unit, waiting time, transfer time in hub point of express commodities are all uncertain. The mathematical model for multimodal service network capacity computation for express shipments with stochastic variables and constraints is formulated. A hybrid intelligent algorithm (HIA) in which Monte Carlo simulation is combined with genetic algorithm (GA) is put forward to solve the proposed model. A numerical case is used to verify the conclusions and the efficiency of solution algorithm.7. Service network of highway-railway transportation for luggage and mail shipping of China Railway Co., Ltd. is taken as a real example to verify the studies in this thesis, which embodies application value and significance of this thesis.