Research On Vehicle Routing Optimization With Three-Dimensional Loading Constraints

Under the policy’s support and economic incentives of the state for the logistics industry,the logistics industry in our country is developing rapidly.Even if the logistics industry develops rapidly,the problem of high logistics costs remains significant.Then the reduction of distribution costs is extremely urgent.The problem of vehicle routing under the constraints of three-dimensional loading has been paid attention to by scholars and industries since it was proposed.However,due to the complexity of the issue,it is still difficult to balance the path and loading problems.This article will build a multi-objective combinatorial optimization model combining the loading and path based on the previous research.Through the solution of the algorithm,the vehicle’s loading scheme and the driving route of the vehicle will be obtained,which will provide reference for the enterprise distribution plan.Firstly,based on the description to the problem of loading and vehicle path optimization and its’ research status and development,this paper integrates 3D loading and vehicle path optimization to establish a multi-objective optimization model which is the shortest vehicle’s route,the maximum load’s utilization and the utilization of the loading space,and in this model the author considers the constraints of customer needs,loading’s order,the vehicle’s size,and the center of gravity of the vehicle and so on.At the same time,the objective function is normalized by introducing the weight coefficient to facilitate the solution of the model.Secondly,in order to solve the established model,we choose the solution algorithm of this paper--genetic algorithm,which is based on the introduction of the characteristics of heuristic algorithm.In this paper,we design the applicable chromosome coding rules,determine the selection,crossover,and mutation methods in genetic manipulation and select the objective function as the fitness function.Simultaneously,in order to prevent the premature convergence of the algorithm,this paper improves the accuracy of the algorithm by introducing the optimal individual preservation strategy.To test and verify the correctness of the model and the effectiveness of design’s algorithm,this paper uses the test data to verify the algorithm and the model’s effectiveness and we have obtained the calculation results by test data which further validates the correctness of the model and the effectiveness of thedesign’s algorithm.Finally,we select the delivery example of Y Logistics Company in Xi’an,Shaanxi Province and Organize customer demand data,location information and vehicle information and so on.At the same time,the solution algorithm designed in this paper is used to solve the delivery solution and compare and analyze fitness function’s variation diagram with different weight coefficients to meet the diversified needs of different customers.The output distribution scheme obtained by the algorithm verifies the effectiveness of the model and algorithm in practical application.