Multi-party ride-matching problem in the ride-hailing market with bundled option services

Abstract

As demands for convenient and comfortable mobility grow, transportation network companies (TNCs) begin to diversify the ride-hailing services they offer. Modes that are offered now include ride-pooling (RP), non-ride-pooling (NP), and a third “bundled” option, which combines RP and NP. This emerging bundled option allows riders to be served via either RP or NP mode, whichever becomes available first. This paper examines the added complexity that a ride-hailing service platform faces when it introduces a third bundled option. Incorporating the predicted pooling information in the near future, a ride-matching problem is dedicated to matching vehicles with riders under various scenarios over a number of matching iterations. We formulate the multi-period ride-matching problem using an integer linear programming model with multiple objectives and to make dispatching decisions based on certain matching criteria. The complexity of the problem requires resolution via a two-stage Kuhn-Munkres (2-KM) algorithm, whose robustness is verified by computational tests. Some interesting insights are obtained: (1) how the bundled option impacts system performance metrics depends on whether the supply is sufficient or not; (2) there is an optimal value of the criterion of the maximum pickup time that maximizes the ride-pooling time savings.