The Optimization Model And Method Of Vehicle Loading Problem

Prosperity and stability of automobile consumption market, promote the appearance of the vehicle logistics industry. The third party vehicle logistics mode, under the fierce competition in the industry and market, has gradually become the preferred mode of transportation. How to reasonably allocate the limited transport capacity and reduce logistics cost, is one of the important ways of the vehicle logistics enterprise to enhance service levels and improve competitiveness and market share. Therefore, this paper study on the optimization model and method of vehicle loading problem for third party logistics based on multi-parameter constraints. The research contents are as following:First, On the basis of theoretical knowledge of vehicle loading optimization, mathematically describing the problems of the loading in view of the actual situation, focusing on the loading carrier of vehicle logistics. Optimizing the geometry feature of the vehicle and finished vehicle and building its mathematical model, and defining the objective function and constraint conditions of loading model.Secondly, the paper studies on optimization algorithm of vehicle logistics for the loading problem. It respectively proposes the optimization method on the basis of constraint conditions. The paper putting forward the order hierarchical clustering heuristic algorithm based on the ideology of cluster analysis, and solving the order batch problem. In view of the FVRP influence, put forward the customer destination FVRP algorithm, and optimization of vehicle routing dynamic effect. In order to improve the solving speed in the loading process, the paper putting forward the improved branch and bound algorithm based on greedy strategy. Comprehensive the above all kinds of heuristic algorithm, and determining a optimization method of vehicle loading problem based on multi-parameter constraints.Finally, the implementation of algorithm by using MATLAB and database knowledge, and analysis of the branch and bound algorithm calculation accuracy and computing speed by comparing the simulation results, reflecting the loading optimization algorithm performance in practical application through application cases and loading results.