Research On The Optimization Of Logistics Vehicle Route

The interconnection of all things is an inevitable trend in the development of the current era.As a physical carrier of the logistics industry,its development level is an important symbol of social modernization.As the main function of the logistics system,the logistics vehicle distribution link is the key to the economic benefits and environment of the entire logistics system.Vehicle routing optimization is an optimization problem involving multiple influencing factors and multi-objective requirements.Among them,the logistics distribution vehicle routing problem with time window constraints is an NP-hard problem.According to the current situation of logistics development,the article will focus on thesingle-lane multi-object vehicle routing optimization problem under the time window and the multi-lane multi-object vehicle routing problem under the time window.Firstly,aiming at the multi-objective optimization problem of single car park under the time window,this paper presents the vehicle distribution path optimization model based on the time window constraint,which takes the distribution distance and distribution time as the objective function,uses the improved C-W saving algorithm to solve the model,and compares it with the traditional C-W saving algorithm,discusses the advantages and disadvantages of various schemes,and gives the practical needs Distribution plan for.For the multi-objective and multi depot vehicle path optimization problem under the time window,considering the diversity of the parking lot,the parking is directly regardedas the distribution center,and the distribution vehicles directly start from the distribution center to serve the customers,and each customer is only served once.After the distribution service is completed,the distribution vehicles can choose torest near the parking lot without returning to the departure parking lot.In the whole distribution process The number of vehicles in each yard needs to be adjusted at any time.Therefore,a multi-objective vehicle routing optimization model is established under the time window,in which the objective function iscarbon emission,distribution cost and number of distribution vehicles.Based onthe above model,an improved particle swarm optimization algorithm is proposed.This algorithm is based on the basic particle swarm optimization algorithm.It updates the linearly decreasing inertia weight to the exponential function inertia weight,and changes the strategy of particle update speed and position.In order toimprove the search ability of the algorithm and avoid local optimization,it is very important to use Pareto dominance relationship The tabu table is introducedto store the non dominated solution,and the crowding distance is calculated todistinguish the merits and demerits of individuals.The particles in the non dominated solution set are stored in the external set by updating the external set.Adjust the order position of thesame non dominated solution,update the global optimal position,the larger the congestion distance,the closer to the optimal solution,to achieve the optimization purpose.Finally,taking company as an example,the case analysis and establishment of the model,through the comparisonbefore and after the improvement of the algorithm.In view of theabove research,this paper summarizes and prospects.