TY - CHAP
T1 - Optimisation for the ride-sharing problem
T2 - 21st European Conference on Artificial Intelligence, ECAI 2014
AU - Simonin, Gilles
AU - O'Sullivan, Barry
N1 - Publisher Copyright:
© 2014 The Authors and IOS Press.
PY - 2014
Y1 - 2014
N2 - The dial-a-ride problem is a classic challenge in transportation and continues to be relevant across a large spectrum of applications, e.g. door-to-door transportation services, patient transportation, etc. Recently a new variant of the dial-a-ride problem, called ride-sharing, has received attention due to emergence of the use of smartphone-based applications that support location-aware transportation services. The general dial-a-ride problem involves complex constraints on a time-dependent network. In ride-sharing riders (resp. drivers) specify transportation requests (resp. offers) between journey origins and destinations. The two sets of participants, namely riders and drivers, have different constraints; the riders have time windows for starting and finishing the journey, while drivers have a starting time window, a destination, and a vehicle capacity. The challenge is to maximise the overall utility of the participants in the system which can be defined in a variety of ways. In this paper we study variations of the ride-sharing problem, under different notions of utility, from a computational complexity perspective, and identify a number of tractable and intractable cases. These results provide a basis for the development of efficient methods and heuristics for solving problems of real-world scale.
AB - The dial-a-ride problem is a classic challenge in transportation and continues to be relevant across a large spectrum of applications, e.g. door-to-door transportation services, patient transportation, etc. Recently a new variant of the dial-a-ride problem, called ride-sharing, has received attention due to emergence of the use of smartphone-based applications that support location-aware transportation services. The general dial-a-ride problem involves complex constraints on a time-dependent network. In ride-sharing riders (resp. drivers) specify transportation requests (resp. offers) between journey origins and destinations. The two sets of participants, namely riders and drivers, have different constraints; the riders have time windows for starting and finishing the journey, while drivers have a starting time window, a destination, and a vehicle capacity. The challenge is to maximise the overall utility of the participants in the system which can be defined in a variety of ways. In this paper we study variations of the ride-sharing problem, under different notions of utility, from a computational complexity perspective, and identify a number of tractable and intractable cases. These results provide a basis for the development of efficient methods and heuristics for solving problems of real-world scale.
UR - https://www.scopus.com/pages/publications/84923136419
U2 - 10.3233/978-1-61499-419-0-831
DO - 10.3233/978-1-61499-419-0-831
M3 - Chapter
AN - SCOPUS:84923136419
T3 - Frontiers in Artificial Intelligence and Applications
SP - 831
EP - 836
BT - ECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings
A2 - Schaub, Torsten
A2 - Friedrich, Gerhard
A2 - O'Sullivan, Barry
PB - IOS Press BV
Y2 - 18 August 2014 through 22 August 2014
ER -