Research On Fault Sharing Bicycle Recycling Problem Based On Reverse Logistics

With the rapid development of the social economy,motor vehicles have become the main choice for people to travel daily,and the traffic congestion and environmental pollution problems caused by this have become increasingly serious.At this time,the sharing bicycle is favored in solving the “last mile” problem of the city because of its quick and convenient,green and environmentally-friendly features.However,in the development of sharing bicycles,some problems have gradually emerged.The most prominent ones at present are the “car-free availability” due to the increasing number of fault bicycles and some environmental problems and the future development of the sharing bicycle industry.The main reason is that due to the lack of scientific and rational planning for the recycling of bicycles,this paper conducts indepth research on the issue of sharing bicycle recycling.This paper firstly analyzes the current situation of the use of sharing bicycles,the main causes of faults and the main problems in the recovery of bicycles in China based on the " Report on China's Sharing Bicycle Industry Market Preview and Investment Planning Analysis " and other sharing bicycle related data,and puts forward the necessity of bicycle recycling.Combined with the logistics characteristics of the sharing bicycle scheduling system,a sharing bicycle recycling system was established.Based on the detailed analysis of the composition and working process of the recycling system,the K-means clustering algorithm was used to determine the initial collection point in the recycling system and to quantify the usage satisfaction of the sharing bicycle users.Then,with the purpose of the shortest recovery path and the maximum customer satisfaction,a sharing bicycle recycling model consisting of the handling cost,transportation cost,recycling vehicle activation cost and customer satisfaction loss cost of the fault-sharing bicycle is established;Through the comparative analysis of the heuristic algorithm for solving the path model,the hybrid genetic algorithm is designed.It is the combination of genetic algorithm and simulated annealing algorithm to solve the model.Finally,the feasibility and effectiveness of the model and algorithm are verified by solving the recovery paths of collected 110 faulty bicycles in parts of Yanta District,Xi'an.Furthermore,through the summary analysis of the full text,the corresponding suggestions for the reasonable recovery of sharing bicycles are put forward.The results show that when the K-means clustering algorithm is used to determine the initial collection point of the recovery system,the maximum distance of the fault point center,the cluster center distance and the F test value of the cluster points 13,14,15 are compared and analyzed.It shows that it is most reasonable to set the number of points to 14.In the recovery path optimization problem,the calculation results show that the path optimization problem with the recovery vehicle start-up cost is not necessarily the shortest path problem in the absolute sense,but the overall cost is optimal;In addition,compared with only using genetic algorithm to solve the recovery model,the hybrid genetic algorithm designed in this paper has lower and more stable calculation results.This also confirms that the recycling scheme built in this paper has certain advantages for the systemization of sharing bicycle recycling and the reduction of sharing bicycle recycling costs.