TSP Problem And Algorithm Selection In Logistics Distribution Vehicle Route Planning

TSP is a complex combination problem,including CTSP(Classical traveling salesman problem)and ATSP(Asymmetric Traveling Salesman Problem).TSP is a closed loop after every vehicle in VRP has been delivered to all stores.In a sense,VRP contains multiple TSP,so solving VRP requires solving multiple TSP.With the continuous increase of the number of TSPs in solving VRP,the solving time will also increase explosively.Therefore,how to determine a short-time and high-stability algorithm for solving TSP in VRP is an urgent problem in the field of logistics distribution.This article mainly conducts in-depth research on the selection of TSP algorithm in logistics distribution VRP.The specific research contents include:(1)The related theories,research status and common solutions of VRP and TSP problems are expounded.At the same time,the number of vehicle combinations,the number of store combinations,and the number of route arrangements are calculated using permutation and combination and tolerance principles.(2)CTSP is the most basic and most important problem in TSP.Based on different actual situations,various types of TSP have been extended based on it.Therefore,this article selects instances within 100 points from the TSPLIB standard database,and selects the angle bisector insertion algorithm,other insertion algorithms,and genetic algorithms for CTSP experiments.The experimental results show that when the solution scale is small,the running efficiency of the angle bisector insertion algorithm and the accuracy of the solution are more superior,but as the solution scale increases,the genetic algorithm has more advantages in time and accuracy than other algorithms.(3)In the field of logistics and distribution,due to the asymmetry of the distance between the stores,the determination of the vehicle's distribution route is to solve the ATSP problem.Therefore,this article selects some ATSP examples from the TSPLIB standard database,and uses the angle bisector insertion algorithm,the farthest insertion algorithm and the genetic algorithm to conduct ATSP experiments.Experimental results show that compared with other algorithms,the angle bisector insertion algorithm can make the calculation results more ideal in a shorter time.(4)This article takes the project of BBG commercial logistics management as an example,uses the actual distribution data in the project,and uses genetic algorithm,farthest insertion algorithm and angle bisector insertion algorithm to conduct VRP experiment.The experimental results show that the angle bisector insertion algorithm has more obvious advantages than the genetic algorithm and the farthest insertion algorithm,which can reduce the running time of the algorithm and has good stability.For the VRP problem,in the process of finding the optimal solution,it is necessary to calculate the TSP in the VRP multiple times and repeatedly compare the calculation results,so the calculation results need to have better stability.In addition,the TSP calculated in VRP is ATSP,and due to the limitation of the loading capacity,the number of stores it distributes is small,which belongs to the solution of small-scale ATSP.In view of the above VRP characteristics,this paper chooses the angle bisector insertion algorithm to solve the TSP in VRP,which can effectively improve the calculation efficiency and has stability.