Research On Multi-modal Express Shipment Network Resource Planning Optimization

With the development of society and economy, together with the optimization of industry structure, the demand of express shipment which is composed by high value-added freight and package grows rapidly and continuously. Moreover, the required service level of the demand also increases. These years, the improvement of railroad, road and air network lay a solid fundation for the construction of high-effective express shipment system. Resource planning for express shipment under multi-modal transportation system, according to the characteristic of each mode, is beneficial to making full use of the advantage of each mode, decreasing the total cost of express shipment system and finally solving the contradiction between the supply and demand.The main contents of the paper includes:(1) The implication of express shipment resource planning problem is analysed, including the characteristics of express shipment supply and demand, the current situation of express shipment industry at home and abroad, the composition of express shipment system, and the definition of express shipment resource. Based on this, the definition, principle and influencing factor of express shipment resource planning.(2) The multi-modal express shipment network resource utilization evaluation problem is investigated. The relationship between frequency of express services and delay time at hub yard is firstly taken into consideration in this paper. Then according to the shipment tranfer operation under different policy, the express shipment service network based on hub node partition and multi-modal transportation is constructed.. Based on this network, the evaluation model which takes service level and generalised cost into consideration is proposed. However, the network and the model should be reconstructed according to the form of the cost function (piece-wise linear or non-linear). The solution strategy which is based on k-shortest path and optimization software Lingo 10.0 is presented to solve the model. Several numerical examples are also presented to test the feasibility and efficiency of solution strategy. The testing result shows that the algorithm can obtain the global optimum of the model and can be applied to large-scale problems.(3) Based on Content (2), the multi-modal express shipment network resource planning optimization problem is investigated. By constructing the express freight service set, the model can be simplified. Aiming at minimizing the total operating cost (including transportation cost and delay cost) and resource planning cost, the express shipment network resource planning optimization model is proposed. The searching space is reduced by service area partition and dividing the nodes into several layers. Four algorithms (Variable neighborhood search, variable neighborhood search based on simulated annealing, neighborhood search based on closed-cycles and algorithm based on k-shortest path and Lingo 10.0) are developed to solve the model. Several numerical examples are presented to test the solution algorithms. The testing result shows that four algorithms have different applicable scope. The decision-maker should choose the best algorithm according to the characteristics and scale of the problem.The multi-modal integrated express hub location and network resource planning optimization model is firstly presented in this paper. This integrated model can take the service network design into consideration when investigating hub location problem. According to the characteristics of the model, a multi-phase solution strategy is proposed to solve the integrated model.(4) Based on Content (3), the multi-modal integrated express shipment network resource and fleet resource planning dynamic optimization problem is investigated. Taking time factor into consideration, a discrete dynamic service network which can describe the fleet utilization plan is constructed. Aiming at minimizing the total operating cost (including transportation cost and delay cost) and fleet cost, the dynamic integrated optimization model is proposed. Then, a decomposition heuristic is developed to break up the original problem into two sub-problem, which affect each other when looking for the optimum. A solution strategy which is based on k-shortest path and Lingo 10.0 is also used to solve the model. Finally, several numerical examples are prestented to test the solution algorithms. The testing results show that although time factor increases the size of the network, the solution strategies presented in the paper can obtain good results within tolerable time and is applicable to practical problem.(5) Based on content (3), the multi-modal express shipment network resource planning problem under stochastic environment is investigated. Under the stochastic demand, aiming at obtain a more robust resource plan, a two-stage stochastic programming model with recourse is proposed to minimizing the expected total cost, including resource planning cost, transportation cost and delay cost. According to the distribution function of the stochastic parameters, three solution strategies, which are decompostion heurisitc based on lagrangian relaxation, algorithm based on k-shortest path and Lingo 10.0 and variable neighborhood search based on sample average approximation, are proposed. Since the third strategy uses stochastic simulation to deal with stochastic parameters, the error is also analysed in the paper. The testing results show that although stochastic programming model is more complex than deterministic programming model, it can obtain a more robust resource plan.