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

Junzhe Huang, Fei Mei, Yazhao Yin, Yuhan Yin, Ze Ouyang, Zhiming Feng, Jianyong Zheng
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Abstract

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.
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考虑碳排放的共享电动自行车多目标鲁棒优化
考虑到共享电动自行车的选址和规模问题,兼顾经济效益和环境效益具有现实意义。首先,确定几个典型场景来模拟共享电动自行车的流通。其次,建立以共享电动自行车企业经济效益最大化和碳排放最小化为目标的多目标优化模型。第三,采用鲁棒优化方法对模型中的需求不确定性进行处理。在此基础上,采用非支配排序遗传算法II(NSGA-II)和模糊隶属度函数求解pareto前沿和最优妥协解。通过算例验证了该模型和算法的可行性。
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