Research On Vehicle Routing Optimization Of Insulated Box Multi-Temperature Joint Distribution

In recent years,the market demand for cold chain products in China has increased rapidly with the improvement of living standards.In order to meet the needs of consumers,cold chain distribution pays more and more attention to reducing distribution costs,reducing goods consumption and improving distribution efficiency.The current single temperature distribution mode has many problems,such as high purchase cost of refrigerated trucks,high loss rate of goods,and can only distribute single temperature goods,which is difficult to meet the market demand for high-quality logistics services.However,the insulated box multi-temperature joint distribution mode uses normal temperature trucks,recyclable cold storage boxes and cold accumulators during distribution,so it can realize multi temperature joint distribution and reduce the distribution cost at the same time.Therefore,it is of great practical significance to study the vehicle routing optimization problem under this mode.Firstly,this thesis sorts out the research status of vehicle routing problem,time window problem,multi temperature distribution problem,split delivery problem and multi center problem,and expounds the theoretical basis of vehicle routing problem,cold chain logistics and insulated box multi-temperature joint distribution.On this basis,this thesis introduces the fuzzy time window constraint,and considers allowing demand splitting to improve the full load rate of distribution vehicles.At the same time,in order to reduce the impact of demand splitting on customer satisfaction,this thesis considers limiting the number of splits,and then establishes a vehicle routing optimization model with limited number of splits in a single distribution center with time window,aiming at minimizing the total distribution cost.Secondly,in order to solve the problem of large distribution pressure in a single center when the customer points are scattered,this thesis establishes a vehicle routing optimization model with limited splitting times of multiple distribution centers with time windows.Then,this thesis designs an improved hybrid genetic algorithm to calculate the two models.When calculating the multi distribution center model,it first uses k-means clustering algorithm to classify customer points,and then use the same hybrid genetic algorithm as the single distribution center model.In this thesis,the improvement of hybrid genetic algorithm includes using the improved optimal insertion method when constructing the initial population;adopts an improved adaptive genetic algorithm;and introduces local search algorithm.Finally,the thesis designs two numerical examples combined with Solomon instance set and uses MATLAB software to solve the two models and verify the examples,which proves the feasibility of the model and algorithm.By comparing the calculation results of the two models,it is proved that the single distribution center model can reduce the number of vehicles and improve the distribution efficiency,when the multi distribution center model can better reduce vehicle mileage and reduce the total cost of distribution.Figure19,Table19,Reference59.