Designing robust routes for demand-responsive transport systems

In this study, we propose an innovative concept for robust demand-responsive transportation (DRT) systems where vehicles may deviate from the planned route to accept late requests, which are unknown during the planning stage. We propose a new formulation of the problem as a stochastic mixed integer program and describe an efficient heuristic procedure that embeds a tabu search approach in a scheme for merging different scenario solutions. The computational results demonstrate the validity of the heuristic and provide useful managerial insights into DRT systems, thereby showing the value of incorporating uncertainty into the planning process.