Research On Multi-objective Logistics Distribution Application Based On Hybrid Ant Colony Algorithm And Disruption Management

Vehicle routing optimization is an important part of the logistics system,which has a significant impact on saving resources,improving distribution efficiency and service levels.However,during the distribution task,distribution vehicles often face many disruptive events,such as the failure of delivery vehicles,customer's cancellation of delivery,and customer's delivery time change,etc.When solving these disruptive events,logistics companies usually only optimize the path with the lowest distribution cost as the goal.But in fact,the disturbance events will have an impact on many factors.If the logistics companies only has a single optimization cost,it will inevitably lead to losses in other aspects.Therefore,when dealing with disturbance events,logistics companies consider multi-objective optimization,which will make the companies get a long-term development.First,this paper builds the customer value evaluation system,and uses K-means algorithm to cluster the customer classification results.Taking the change of customer time window as a disruptive event of logistics distribution,the paper considers the three goals of customer satisfaction,path deviation and cost deviation,and constructs a disturbance management model based on multi-object dictionary sorting.According to the idea of disturbance management,the disturbance identification method,disturbance measurement and disturbance strategy are proposed,and the paper proposes a disturbance measurement that combines customer value theory and prospect theory.Then,the hybrid ant colony algorithm(ACO-SA)is proposed by combining ant colony and simulated annealing algorithm.The algorithm improves the state transition rules and pheromone update methods.According to the optimal solution,the simulated annealing algorithm is used to dynamically adjust the parameters of the ant colony algorithm.These improved strategies are helpful to improve the performance of ant colony algorithm and solve the vehicle problem.Finally,the effectiveness of the hybrid ant colony algorithm and disruption management model is verified by using literature data.In order to further verify the performance of the algorithm,the effectiveness of the hybrid ant colony algorithm is verified by comparing with other literature data,Solomon examples and other algorithms.In addition,the logistics scheduling management system is developed according to the actual demand of logistics distribution.The system uses the SSM framework technology to help complete the construction of all functions and facilitate the management of all information;The Matlab GUI program uses the hybrid ant colony algorithm as the distribution algorithm to generate the scheme of minimizing the running cost.Java Script technology helps show the delivery route of the delivery vehicle in the actual map throughBaidu API.As a whole,the logistics scheduling management system can realize information input,generation of distribution scheme,information management and other functions.