Systematic review categorizes bicycle-sharing rebalancing methods across operational domains, highlighting pathways for dynamic, feedback-driven mobility management.
Key Points
Synthesize existing research on bicycle-sharing rebalancing strategies across multiple operational dimensions and identify prospective directions to improve system efficiency.
Conducted a systematic review categorizing literature into four distinct strands: static rebalancing under deterministic demand, dynamic rebalancing under deterministic demand, rebalancing under demand uncertainty, and user-based rebalancing.
Evaluated the objectives, core assumptions, mathematical formulations, and canonical algorithmic solution routines across each operational strand.
Identified critical gaps across current methodologies, notably in managing adaptive temporal granularity, balancing robustness with operational efficiency, and accounting for user response delays.
Outlined prospective research paradigms, including feedback-enabled rebalancing, behavior-aware incentive structures, and hybrid governance within an integrated decision framework.