The problem of designing a rebalancing algorithm for a large-scale ridehailing system with asymmetric (unbalanced) demand is considered here. We pose the rebalancing problem within a semi Markov decision problem (SMDP) framework with closed queues of vehicles serving stationary, but asymmetric...

A clustering-based undersampling (CUS) and distance-based near-miss method are widely used in current imbalanced learning algorithms, but this method has certain drawbacks. In particular, the CUS does not consider the influence of the distance factor on the majority of instances, and the...