Research And Design Of Material Distribution Path Planning Method

Material distribution has important applications in emergency disaster rescue and military material distribution.Drone and drone-based equipment based on radio communications can complete the distribution tasks of complex areas and space environments with high quality through pre-planning distribution routes.The distribution problem is the problem of vehicle path planning.Its research goal is to plan the distribution path that meets certain constraints and meets the needs of task.According to different disaster situations and military war situations,many distributions need to be completed within a specified time period,so different types of vehicle routing problems such as vehicle routing planning with time windows have arisen.This thesis studies the problem of vehicle path planning.Its main research content is as follows:(1)Research background and significance.The paper introduces the definition of material distribution,and the research background and research importance of material distribution in the field of disaster and military application.Research methods for vehicle path planning problems,as well as domestic and foreign research status of inspiration methods.In terms of inspiration method research,the paper focuses on the basic principles and implementation steps of commonly used algorithms from two aspects.Among them,the group-based heuristic methods include genetic algorithm,ant colony algorithm and artificial bee colony algorithm;the individual-based heuristic algorithm introduces simulated annealing algorithm and tabu search algorithm.(2)Description and solution of vehicle routing problem with time window.According to the characteristics and solution requirements of the problem,the paper designs a genetic algorithm to solve this problem,and conducts simulation experiments based on the four types of customer number problems of 15,30,50 and 100,which verifies the effectiveness of the algorithm,but the effect of solving large-scale problems poor.(3)On the basis of genetic algorithms,the paper adds a large-scale neighborhood search algorithm,and at the same time mixes the K-MEANS algorithm.The improved algorithm is referred to as LNSGA-K.Testing the after-improvement algorithm and comparing the experimental results before the improvement,the effectiveness and excellence of the LNSGAK algorithm is verified,the defects of the weak ability of the genetic algorithm bureau to find the ability of the priority of the genetic algorithm,and improve the performance of the algorithm.Compare the LNSGA-K algorithm with other algorithms of the same algorithm and the optimal solution.The LNSGA-K algorithm designed in this thesis can effectively solve the problem of time window vehicle path problems and is more excellent.(4)Based on the simultaneous pickup and delivery problem,the vehicle routing problem with time window is further introduced into the simultaneous pickup and delivery vehicle routing problem with time window.Based on the LNSGA-K method,the optimization ability of the algorithm is further enhanced by introducing the simulated annealing algorithm.The improved algorithm is called ILNSGA-K for short.The paper uses the ILNSGA-K algorithm to solve 8VRP with simultaneous pick-up and delivery with time window problems.After simulation tests and comparative analysis,the improved method ILNSGA-K is better than the unimproved method.(5)Research and design of vehicle path planning simulation test platform,using the GUI function of MATLAB,design a path planning platform that can solve the problem with time window and the problem of simultaneous pickup and delivery with time window.The path algorithm and the results display the four modules.Through the simulation test,the platform works effectively,and the simple and intuitive interface can conveniently provide users with vehicle route planning solutions.