Research On Vehicle Routing Problem Of Simultaneous Delivery And Pickup

With the rapid development of science and technology and the continuous progress of society,the profits of logistics enterprises are constantly improving,and people pay more attention to the rationalization and efficiency of logistics.It is of great theoretical value and practical significance to make a reasonable logistics distribution plan and reduce the distribution cost.The traditional vehicle routing problem only distributes goods without recycling.In order to avoid the waste of resources caused by no-load and repeated transportation in the process of vehicle distribution,many enterprises consider the distribution and recycling of goods.Therefore,this paper studies the integrated vehicle routing problem of loading and unloading.The main research contents are as follows:(1)Research on vehicle routing problem of basic loading and unloading integration.Firstly,the mathematical model of VRPSDP is given,and an improved bacterial foraging algorithm is proposed to solve the problem.In order to solve the overload problem in the integrated vehicle routing problem,and to make more effective use of the loading capacity of vehicles,when constructing the initial solution,according to the priority arrangement of customers with large delivery demand and small pick-up demand or postponement arrangement of customers with large pick-up demand and small delivery demand,we,The customers are pre sorted according to the "delivery quantity / pick-up quantity" from large to small,and the insertion algorithm is used to insert customers into the path in turn according to the pre sorting order;In the later optimization stage,the chemotaxis operation of bacterial foraging algorithm is combined with the designed inter path search operator and intra path search operator for optimization.The inter path search operator and intra path search operator are randomly selected as the direction of chemotaxis operation,and the path is constantly updated to find the optimal solution;Finally,MATLAB software is used to carry out simulation experiments to verify the performance of the improved algorithm through Salhi and Nagy standard test sets,and compared with the improved particle swarm optimization algorithm,saving heuristic algorithm,generalized saving heuristic algorithm and extended parallel heuristic algorithm.From the overall point of view,92% of CMTX cases are better than the comparison algorithm,and 85% of CMTY cases are better than the comparison algorithm,It is proved that the improved bacterial foraging optimization algorithm is feasible in solving VRPSDP problem,which provides a better guidance scheme for each logistics enterprise’s path planning problem.(2)Research on vehicle routing problem with simultaneous delivery pickup and time windows(VRPSDPTW).Firstly,the mathematical model of VRPSDPTW is established,and an adaptive large neighborhood search algorithm based on simulated annealing mechanism is proposed to solve the problem.In the initial deconstruction,based on the different location distribution of customer nodes,this paper uses two methods to construct,one is greedy insertion method based on K-means,the other is insertion algorithm based on distance and time weighting;In the optimization stage,the deletion operator and insertion operator designed in the adaptive large neighborhood search algorithm are used to dynamically optimize the initial solution,and the simulated annealing mechanism is used to control the update of the solution;Finally,MATLAB software is used to carry out simulation experiments,and VRPSDPTW standard data set is used to verify the feasibility of the algorithm.Compared with genetic algorithm,parallel simulated annealing algorithm,discrete cuckoo algorithm,basic artificial fish swarm algorithm,improved global artificial fish swarm algorithm and Two stage algorithm,when compared with the above algorithms,in the test set Solomon example,85% of the R cases are better than the comparison algorithm,91% of the C cases are better than or the same as the comparison algorithm,and 77% of the RC cases are better than the comparison algorithm.Therefore,the performance of the algorithm in this paper is effective,which can provide some guidance for the distribution scheme of logistics enterprises.