A multi-objective optimization framework for online ridesharing systems

The ultimate goal of ridesharing systems is to match travelers who do not have a vehicle with those travelers who want to share their vehicle. A good match can be found among those who have similar itineraries and time schedules. In this way each rider can be served without any delay and also each driver can earn as much as possible without having too much deviation from their original route. We propose an algorithm that leverages biogeography-based optimization to solve a multiobjective optimization problem for online ridesharing. It is necessary to solve the ridesharing problem as a multi-objective problem since there are some important objectives that must be considered simultaneously. We test our algorithm by evaluating performance on the Beijing ridesharing dataset. The simulation results indicate that BBO provides competitive performance relative to state-of-the-art ridesharing optimization algorithms.