Research And Application Of Railway Express Goods Distribution Path Optimization Under Loading Constraints

The rapid development of information industry and e-commerce as well as the change of customer’s consumption concept have made customers put forward higher requirements for the convenience of logistics services,and services such as door-to-door delivery have become the normal for customer needs.In order to seize the freight market,China National Railway Group Co.,Ltd.vigorously advocates freight reform,promotes railroad express products,and proposes a "door-to-door" transportation mode to better meet customer needs,but due to the limited resources of its own vehicles,end distribution management is not fine and other issues exist,resulting in the uneconomical railroad end distribution.It is necessary to reasonably optimize the distribution route,optimize the vehicle loading utilization rate and reduce the logistics cost.In this paper,the two NP problems of loading optimization and route optimization are jointly considered,and a multi-objective joint optimization model with the lowest transportation cost,the lowest number of vehicles used and the greatest customer satisfaction is established based on the constraints of cargo size,loading order and center of gravity range.Combining with the characteristics of railroad express cargo,the loading mode of heavy bottom and light top with full contact on the bottom surface is proposed to minimize cargo damage and improve the satisfaction of distribution.At the same time,this paper changes the previous multi-objective weighted transformation into single-objective solution idea,and instead uses the multi-objective joint solution to design the algorithm to solve the multiobjective problem directly,which avoids the subjective interference brought by parameter setting.In terms of problem solving,this paper takes NSGA II as the main body of the algorithm and designs a combined nested algorithm combined with the tree search algorithm to solve the joint optimization problem.To avoid the situation of falling into local optimum due to the nonoptimal initial solution,the greedy algorithm is used to obtain the initial solution.In the design of the packing algorithm,this paper takes the tree search algorithm as the main body,draws on the idea of the deepest-bottom-left-Full heuristic to set the heuristic operator,and loads the cargo of the cargo owner by continuously dividing the space and merging the effective space,and at the same time,combining the characteristics of the large volume of single cargo owner of railroad express cargo and more cargo of the same size,the combination module is used to optimize the loading process,and the cargo of the same size of the same kind is The loading efficiency is improved by combining the same size cargoes and loading them as a whole.Finally,the algorithm is used to solve the actual distribution data of China Railway Express Chengdu Branch on a certain day,and several solutions are selected in the Pareto frontier solution set for analysis and illustration,and the solution of distribution and loading map are output.For the solution results of the algorithm,the enterprise can choose different solutions according to the different focus of the distribution requirements,and verify the effectiveness of the model and algorithm in the actual problem.