Maximising the number of participants in a ride-sharing scheme: MIP versus CP formulations

Thumbnail Image
ictai15.pdf(1.43 MB)
Accepted Version
Armant, Vincent
Mahbub, Nahid
Brown, Kenneth N.
Journal Title
Journal ISSN
Volume Title
Published Version
Research Projects
Organizational Units
Journal Issue
Ride sharing schemes aim to reduce the number of cars in congested cities, while providing the participants with a cheaper alternative to solo driving. To ensure a ride-sharing scheme thrives, it is important to maintain a high participation rate. This requires an adequate balance between drivers and riders. And thus ride matches should be proposed which maximize the number of participants. Different variants of the ride sharing problem have been solved using mixed integer programming. In this paper, we introduce a constraint programming formulation for the problem that uses cumulative constraints with dependencies between trip times. In experiments based on collected trip schedules from four different regions, the constraint model outperforms the MIP model. However, when we change the problem by assuming all drivers have flexible roles, the MIP model allows faster solution times than the CP model.
Ride-sharing optimization , Constraints
Armant, V., Mahbub, N. and Brown, K. N. Maximising the number of participants in a ride-sharing scheme: MIP versus CP formulations. Tools with Artificial Intelligence (ICTAI), 2015 IEEE 27th International Conference, Vietri-Sul-Mare Italy, 9-11 Nov. 2015. 836-843. doi: 10.1109/ICTAI.2015.123
© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.