Shared Bikes Scheduling Under Users’ Travel Uncertainty

With the rise of green concept, shared bikes are booming. The accompanying unbalanced scheduling problem is a scientific problem that needs to be solved urgently. Aiming at the problem of shared bikes scheduling with travel uncertainty, a multi-objective integer programming model is established based on the consideration of static demand of fix time period, station capacity limit, penalty cost and other practical factors. In addition, this paper gives the basic formula to calculate the parameters in the model. An algorithm based on “ant colony algorithm” is then given to solve the model. Taking the massive data provided by the “Mobike” company in 2017 as an example, this paper uses the program analysis data to prove the feasibility and effectiveness of the model and get the initial optimization plan. Finally, the data simulation is carried out to verify the feasibility and accuracy of the optimization scheme and the optimization scheme is adjusted accordingly to obtain the final optimization scheme. The research results show that the final optimization scheme proposed in this paper has certain reference value for the scheduling problem of Shanghai “Mobike”.