Design And Implementation Of Urban Express Delivery And Takeaway Delivery Route Planning Management System

With the rapid expansion of e-commerce and take-out platform,urban express delivery and take-out has become an important component of the logistics service system.Due to the large number of customers,more optimization goals and constraints,resulting in higher distribution costs,delivery timeouts and other issues,the complaints generated seriously affect the healthy development of related industries.The design and implementation of express delivery route planning management system is imminent.However,the existing route planning algorithms have many problems,such as ambiguous objectives and low computational efficiency.For this reason,this paper proposes two route planning algorithms for express delivery and take-out delivery,and designs and completes the express delivery and take-out route planning management system based on these two algorithms.1.A two-stage multi-objective genetic algorithm based on courier.The optimization objectives are: the minimum number of vehicles,the shortest distance,the least working time,the shortest waiting time and the shortest late time.The algorithm is used to solve the multi-objective express delivery vehicle routing problem with time windows for multiple delivery stations.The first phase of the algorithm is based on a reference pointbased genetic algorithm,which is combined with the area of interest,local search and gradient estimation methods to improve the convergence of the algorithm.In the second stage,based on decomposition-based multi-objective evolutionary algorithm,the algorithm is combined with neighborhood structure,crossover operator,local search and archiving mechanism to maintain diversity and avoid local optimization.2.A takeaway-based pheromone crossover operator genetic algorithm.This algorithm is used to solve the delivery route problem of take-out vehicles with time windows.Based on genetic algorithm,the traditional genetic algorithm is combined with local search and pheromone-based crossover operator to improve the calculation speed and avoid local optimization.At the same time,the parameter setting method of pheromone-based crossover operator is obtained through many experiments,which can achieve better results in the mutation evolution phase of the genetic algorithm than the conventional scheme.3.Path planning management system based on this algorithm.The system consists of four parts: client,service and mobile.Clients face customers and collect customer order information.The server faces employees,manages and exports data,and plans distribution routes according to algorithms.The mobile end provides multipoint path navigation.The Web uses SSH framework,the front end uses Div and CSS technology,the Ajax technology and DWR framework are used interactively,and the multi-point navigation mobile end uses Android development platform.