Research On Logistics Delivery Path Optimization Based On Improved Genetic Algorithm

With the continuous development of society,online shopping is no longer limited to shopping platforms such as Taobao and JD.com.Various live streaming platforms have also added the function of carrying goods.These various shopping methods have also led to the rapid development of the logistics industry.As a core position in the logistics industry,logistics transportation accounts for most of the costs in the entire process.Therefore,how to plan vehicles and distribution routes reasonably has a direct impact on logistics companies.In response to the above issues,relevant theories of logistics distribution vehicle routing problems were studied,and vehicle routing problems with different constraint conditions were classified.The basic operating steps,advantages,and disadvantages of genetic algorithms were studied.Finally,this article achieved reasonable planning of vehicle routing through adaptive hybrid genetic algorithms.The main research content includes the following aspects.(1)Aiming at the shortcomings of weak local search ability and easy convergence of genetic algorithm,and based on the current adaptive adjustment strategy,unreasonable parameters caused by not considering the iterative process,the number of iterations is added to the adaptive adjustment formula to control the parameters of the algorithm in different periods,including the stretching of the fitness function,the adaptive elite retention strategy,and the adaptive crossover probability and mutation probability,And a test function was selected to test the solving efficiency of the improved algorithm.(2)Applying adaptive genetic algorithm to solve CVRP problems and combining it with variable neighborhood search algorithm to generate initial solutions to accelerate the algorithm’s solving speed.In order to maintain path integrity and enhance algorithm search capabilities,a POX crossover method combining single point interception and two points interception is adopted to construct the substring.Finally,after the genetic operation is completed,the variable neighborhood search algorithm is used to optimize the population individuals.Finally,data from the public dataset CVRPLIB was selected for testing,verifying the effectiveness of the algorithm and applying it to actual company scenarios.This article discusses the capacitated vehicle routing problem,which is of great practical significance for logistics enterprises’ distribution tasks.By arranging the distribution vehicle routing reasonably,it can reduce transportation costs,improve distribution efficiency,and to some extent reduce carbon emissions and environmental pollution.