Stable Matching for Dynamic Ride-sharing Systems
Xing Wang,
Niels Agatz and
Alan Erera
ERIM Report Series Research in Management from Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam
Abstract:
Dynamic ride-sharing systems enable people to share rides and increase the efficiency of urban transportation by connecting riders and drivers on short notice. Automated systems that establish ride-share matches with minimal input from participants provide the most convenience and the most potential for system-wide performance improvement, such as reduction in total vehicle-miles traveled. Indeed, such systems may be designed to match riders and drivers to maximize system performance improvement. However, system-optimal matches may not provide the maximum benefit to each individual participant. In this paper we consider a notion of stability for ride-share matches and present several mathematical programming methods to establish stable or nearly-stable matches, where we note that ride-share matching optimization is performed over time with incomplete information. Our numerical experiments using travel demand data for the metropolitan Atlanta region show that we can significantly increase the stability of ride-share matching solutions at the cost of only a small degradation in system-wide performance.
Keywords: ride-sharing; carpooling; sustainable transport; stable matching (search for similar items in EconPapers)
Pages: 34
Date: 2015-05-27
New Economics Papers: this item is included in nep-gth and nep-tre
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:ems:eureri:78193
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