Recycling scheduling of urban damaged shared bicycles based on improved genetic algorithm

There are many problems in the maintenance of urban-shared bicycles, such as uncertain damage degree, wide distribution and so on. Urban-shared bicycles do not have a complete set of reverse logistics recovery model. To solve this problem, this paper proposes a new maintenance management scheme. Firstly, this paper makes a quantitative analysis based on the damage degree of each shared bicycle. Secondly, the maintenance centre assigns maintenance tasks according to the repair capacity of each inspection vehicle. Thirdly, a new improved genetic algorithm is designed to solve the problem based on the Pareto Principle of wealth imbalance. Finally, the improved algorithm is compared with the classical algorithm for the performance of solving the problem. Experimental results show that the improved algorithm can effectively solve the recycling scheduling problem under the constraint of maintenance ability, and it has higher convergence and stability than the classical algorithm.