Multi-day fair collaboration in demand-responsive transportation

In this paper, we consider the case of companies that offer a demand-responsive transportation service, such as a shared-taxi service, and are engaged in a horizontal collaboration initiative. The goal of the coalition is to optimize the transportation operations in such a way that no company is penalized, in terms of customers served and/or working time. We present an optimization model for a multi-day planning horizon that includes constraints aimed at guaranteeing a level of fairness to all companies that can be controlled over the planning horizon and day-by-day, if beneficial. An adaptive large neighborhood search heuristic is then presented for its solution. The computational experiments show that, although the model constraints the optimization space, it still guarantees substantial savings. Moreover, they show that the model is flexible and can guarantee the sustainability in the long term of the collaboration initiative.