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dc.contributor.advisorDimitris J. Bertsimas and Vivek F. Farias.en_US
dc.contributor.authorTrichakis, Nikolaos Ken_US
dc.contributor.otherMassachusetts Institute of Technology. Operations Research Center.en_US
dc.date.accessioned2011-12-19T18:49:09Z
dc.date.available2011-12-19T18:49:09Z
dc.date.copyright2011en_US
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/67769
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2011.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 131-136).en_US
dc.description.abstractThis thesis deals with two basic issues in resource allocation problems. The first issue pertains to how one approaches the problem of designing the "right" objective for a given resource allocation problem. The notion of what is "right" can be fairly nebulous; we consider two issues that we see as key: efficiency and fairness. We approach the problem of designing objectives that account for the natural tension between efficiency and fairness in the context of a framework that captures a number of problems of interest to operations managers. We state a precise version of the design problem, provide a quantitative understanding of the tradeoff between efficiency and fairness inherent to this design problem and demonstrate the approach in a case study that considers air traffic management. Secondly, we deal with the issue of designing implementable policies that serve such objectives, balancing efficiency and fairness in practice. We do so specifically in the context of organ allocation for transplantation. In particular, we propose a scalable, data-driven method for designing national policies for the allocation of deceased donor kidneys to patients on a waiting list, in a fair and efficient way. We focus on policies that have the same form as the one currently used in the U.S., that are policies based on a point system, which ranks patients according to some priority criteria, e.g., waiting time, medical urgency, etc., or a combination thereof. Rather than making specific assumptions about fairness principles or priority criteria, our method offers the designer the flexibility to select his desired criteria and fairness constraints from a broad class of allowable constraints. The method then designs a point system that is based on the selected priority criteria, and approximately maximizes medical efficiency, i.e., life year gains from transplant, while simultaneously enforcing selected fairness constraints. Using our method, we design a point system that has the same form, uses the same criteria and satisfies the same fairness constraints as the point system that was recently proposed by U.S. policymakers. In addition, the point system we design delivers an 8% increase in extra life year gains. We evaluate the performance of all policies under consideration using the same statistical and simulation tools and data as the U.S. policymakers use. We perform a sensitivity analysis which demonstrates that the increase in extra life year gains by relaxing certain fairness constraints can be as high as 30%.en_US
dc.description.statementofresponsibilityby Nikolaos K. Trichakis.en_US
dc.format.extent136 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectOperations Research Center.en_US
dc.titleFairness in operations : from theory to practiceen_US
dc.title.alternativeFairness in operations.en_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Operations Research Center
dc.contributor.departmentSloan School of Management
dc.identifier.oclc767527418en_US


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