Optimization Models And Algorithms For Freight Transportation Service Network Design

Service network design is used to address tactical planning issues of the freight transportation system.It is widely applied in transportation,logistics,production,and other fields,and involves large transportation networks including a large number of vehicles and people.As the logistics enterprises keep improving their transportation networks to covers more regions across the country,it is particularly important to optimize the transportation network to reduce the operating costs of transportation services.With the rapid development of China's e-commerce,the behaviors of consumers are affected by the promotion of merchants,holidays and other factors,resulting in great fluctuations in demand,which brings great challenges to the planning and design of express delivery and less-than-truck cargo transportation service networks.This dissertation first studies the large-scale service network design problem considering a heterogeneous fleet,which helps enterprises determine the number of different types of vehicles used in each transportation service.A mixed integer programming mathematical model is constructed for the problem,which is solved efficiently by a hybrid algorithm.The proposed algorithm combines column generation and cutting plane algorithms to provide better lower bounds and employs the local search method to find high-quality feasible solutions.Numerical experiments show the effectiveness of the proposed algorithm.The case study indicates that considering a heterogeneous fleet can help enterprises reduce the total cost,which reflects the practical significance of this research.In order to reduce the transportation risk,especially for the transportation of dangerous goods,and to facilitate the delivery and customer receipt of goods,the single-path constraints are considered for service network design,and a mathematical model based on cycle-path is proposed.An exact algorithm is designed to provide tight lower bounds,and a variable-fixing method is used to reduce the size of the problem,making it easier to solve the problem to find high-quality feasible solutions efficiently.The effectiveness of the algorithm is evaluated through numerical experiments.Regarding service network design considering uncertain demands,the polyhedral uncertainty set is used to describe demand uncertainty,and a two-stage robust optimization formulation is introduced.A column-and-constraint generation algorithm is employed to solve the proposed robust optimization model,which can provide the upper and lower bounds of the model in each iteration.Numerical experiments show that the column-andconstraint generation algorithm has good performance in both computational time and solution quality.The structural characteristics of robust solutions are analyzed,and the results of model comparison also show the superiority of robust solutions.Last,in order to design an integrated service network to improve the utilization rate of resources such as vehicles in the system,both deterministic and two-stage robust optimization models are proposed for service network design considering multiple service types.The column-and-constraint generation algorithm is implemented to solve the proposed robust model,and the impact of considering multiple service types on the transportation system is analyzed.Numerical experiments show that the diversification of service types in the transportation system is helpful to reduce the total cost and the number of vehicles used in the network.