Multi-objective Robust Optimization of Siting and Sizing for Shared Electric Bikes Considering Carbon Emission

Considering the problem of the siting and sizing of shared electric bikes, it is of practical significance to take into account both the economic and environmental benefits. Firstly, several typical scenarios are determined to simulate the circulation of shared electric bikes. Secondly, a multi-objective optimization model is established, which aims at maximizing economic benefits of the shared electric bike enterprise and minimizing carbon emissions. Thirdly, the demand uncertainty in the model is processed by robust optimization method. On this basis, non-dominated sorting genetic algorithm II(NSGA-II) and fuzzy membership function are used to work out the pareto front and the optimal compromise solution. The feasibility of the model and algorithm is verified by a numerical example.