Robust Approaches To Operations Management In Bike-Sharing Systems

The emergence of shared travel modes allows users to access and share resources without owning them.A bike-sharing system is an example of a shared mobility mechanism that provides an alternative transportation mode for short trips.Although a number of cities worldwide have adopted public bike-sharing systems over the last decade,the high initial investment cost,low profitability and bike usage ratio restrict the development of bike-sharing systems.Recently,benefit from the information techniques and mobility payments,the bike-sharing systems have been developed on a large scale.According to the current status of bike-sharing systems,in this research,we aim to provide decision support for managers from different decision perspectives.In detail,we first focus on the question “How to improve the operation efficiency of bikesharing systems”,and present a new robust integrated station location and rebalancing vehicle service design model.Based on the practical fleet operations,this model resolves the inconsistence in rebalancing operations at the strategic and operational decisions.Besides,we further build a robust model to consider a demand-related uncertainty set and design a row generation approach to solve it.The results of numerical study illustrate that the station distribution in each service area does not have to be confined to one geographical area but depends on the demand levels.Second,to fill the gap that no research studies on the relationship between the operating modes and system profitability,we pay attention to answer the question “Which operating mode of the operating modes has the best performance under various different sets of conditions and demand uncertainty”.We summarize the features of three different operating modes(station-based,free-float and hybrid)and use the queue analysis to describe the user behaviours.Then a unified multi-state model is presented to formulate these three operating modes by different combinations of the constraints and parameter settings.An adjustable distributional robust counterpart is further formulated to consider demand ambiguity.The results of numerical study show that each operating mode has its own range of applications.Hence,this model offers a theoretical support for deciders to select an appropriate operating mode.Third,we analyze the profitability problem of a bike-sharing provider when it expands a new market.The study on this problem can help to evaluate the efficiency of system and answer the question “Whether a bike-sharing firm should expand market in a new region”.We provide a multi-stage robust nonlinear model to determine the dynamic bike inventories over the operation periods under uncertainty in the operation policies of other providers.User choice behaviours between these bike-sharing systems are also considered.To solve this nonlinear model,we first consider the special case with two periods,which can be solved by a customized constraint-and-column generation approach.Then a myopic method is presented to solve the multi-state model and obtain a tight gap between the upper and lower bounds of the true objective value.The results of numerical study demonstrate that when the depreciation cost is high and the local firm increases the bike acquisition,the new bike-sharing firm should reduce the number of bikes to maximize the revenue.Hence,in this research,we explore the relationship between some influencing factors and system operations,and present several optimization models to improve the profitability and robustness of the bike-sharing systems.