On-demand transportation systems enable vehicles to choose where to meet customers. This flexibility offers opportunities to design new service offerings but, at the same time, requires coordination between vehicles and customers that adds complexity to routing operations. This talk explores this question in two areas: ride-sharing and microtransit. First, we develop scalable algorithms to optimize routing operations with vehicle-customer coordination in ride-sharing, combining a tailored coordinate descent scheme and a novel subpath-based time-space network optimization approach. The algorithm outperforms state-of-the-art benchmarks, yielding far superior solutions in shorter computational times. Results suggest that vehicle-customer coordination can provide win-win-win outcomes: higher profits, better customer service, and smaller environmental footprint. Second, this talk formulates a two-stage stochastic optimization model to support network design in microtransit systems in the presence of on-demand demand-responsive routing adjustments. Again, results suggest that microtransit systems can provide win-win-win benefits in urban mobility: higher demand coverage, lower operating costs, and smaller environmental footprint.

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