  The ultimate goal of ridesharing systems is to matchtravelers who do not have
a vehicle with those travelers whowant to share their vehicle. A good match can
be found amongthose who have similar itineraries and time schedules. In thisway
each rider can be served without any delay and also eachdriver can earn as much
as possible without having too muchdeviation from their original route. We
propose an algorithmthat leverages biogeography-based optimization to solve a
multi-objective optimization problem for online ridesharing. It isnecessary to
solve the ridesharing problem as a multi-objectiveproblem since there are some
important objectives that must beconsidered simultaneously. We test our
algorithm by evaluatingperformance on the Beijing ridesharing dataset. The
simulationresults indicate that BBO provides competitive performancerelative to
state-of-the-art ridesharing optimization algorithms.
