Conclusions and Outlook

Abstract

This work lays the foundation for SND of BSS and related SMS. Designing a service network requires the suitable aggregation of operational data as well as the anticipation of operational decisions. Therefore, an integrated approach of IDA and mathematical optimization for SND of BSS has been proposed. The presented IM allows for the generation of demand scenarios in terms of typical bike flows. Derived scenarios serve as input for SND optimization. The MIP-based SND optimization model determines the optimal fill level at stations in the course of the day minimizing the expected costs of relocation services while ensuring a predefined service level.