Generating Efficient Rebalancing Routes for Bikeshare Programs Using a Genetic Algorithm

Growth in urban areas often leads to problems such as increased traffic congestion and poor air quality. To help alleviate these issues, shared mobility networks have been launched in hundreds of cities worldwide to provide citizens with alternatives to personal autos and to other less sustainable methods of transport (Fishman, 2016; Zhang et al., 2015). Shared mobility includes carsharing, ridesharing, scooter sharing and bikesharing (SAE, 2018). Bikeshare programs allow users to pick up bicycles (often at hub locations), utilize the bicycle for a journey, and return it to a location within the system (DeMaio, 2009). While bicycle sharing has been in existence for many years in various forms, the advent of modern telecommunications (i.e., cellular technology and the internet) have enabled these programs to proliferate.