In view of the shortage of intelligent parking spots for shared bicycles in rush hours

a parking spot allocation algorithm based on improved genetic algorithm is proposed. The local search ability of genetic algorithm is easy to be precocious in solving optimization problems. Therefore

the linear regression algorithm is integrated into the genetic algorithm to increase the direction of individual variation and accelerate the convergence speed of the genetic algorithm

so as to avoid the traditional genetic algorithm fall into local optimum

and the performance of the algorithm is improved. Finally

through the simulation experiment

the convergence speed of the distribution model is accelerated

the time resources in the parking point allocation problem are saved

and the dynamic realtime performance of the parking point information is guaranteed.