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Models and Algorithms for Transportation in the Sharing Economy

dc.contributor.authorFreund, Daniel
dc.contributor.chairShmoys, David B.
dc.contributor.committeeMemberWilliamson, David P.
dc.contributor.committeeMemberKleinberg, Jon M.
dc.date.accessioned2018-10-23T13:34:19Z
dc.date.available2018-10-23T13:34:19Z
dc.date.issued2018-08-30
dc.description.abstractThis thesis consist of two parts. The first deals with bike-sharing systems which are now ubiquitous across the U.S.A. We have worked with Motivate, the operator of the systems in, for example, New York City, Chicago, and San Francisco, to innovate a data-driven approach to managing both their day-to-day operations and to provide insight on several central issues in the design of their systems. This work required the development of a number of new optimization models, characterizing their mathematical structure, and using this insight in designing algorithms to solve them. Many of these projects have been fully implemented to improve the design, rebalancing, and maintenance of Motivate’s systems across the country. In the second part, we study a queueing-theoretic model of on-demand transportation systems (e.g., Uber/Lyft, Scoot, etc.) to derive approximately optimal pricing, dispatch, and rebalancing policies. Though the resulting problems are high-dimensional and non-convex, we develop a general approximation framework, based on a novel convex relaxation. Our approach provides efficient algorithms with rigorous approximation guarantees for a wide range of objectives and controls.
dc.identifier.doihttps://doi.org/10.7298/X47S7M1X
dc.identifier.otherFreund_cornellgrad_0058F_10983
dc.identifier.otherhttp://dissertations.umi.com/cornellgrad:10983
dc.identifier.otherbibid: 10489721
dc.identifier.urihttps://hdl.handle.net/1813/59625
dc.language.isoen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectApplied mathematics
dc.subjectAlgorithms
dc.subjectOptimization
dc.subjectComputer science
dc.subjectTransportation
dc.subjectOperations research
dc.subjectStochastic modeling
dc.subjectData Science
dc.subjectSharing Economy
dc.titleModels and Algorithms for Transportation in the Sharing Economy
dc.typedissertation or thesis
dcterms.licensehttps://hdl.handle.net/1813/59810
thesis.degree.disciplineApplied Mathematics
thesis.degree.grantorCornell University
thesis.degree.levelDoctor of Philosophy
thesis.degree.namePh. D., Applied Mathematics

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