Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/25894
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dc.contributor.authorLodi, Andrea
dc.contributor.authorOlivier, Philippe
dc.contributor.authorPesant, Gilles
dc.contributor.authorSankaranarayanan, Sriram
dc.date.accessioned2022-11-14T04:14:17Z
dc.date.available2022-11-14T04:14:17Z
dc.date.issued2022-11-07
dc.identifier.citationLodi, A., Olivier, P., Pesant, G. et al. Fairness over time in dynamic resource allocation with an application in healthcare. Math. Program. (2022). https://doi.org/10.1007/s10107-022-01904-6en_US
dc.identifier.issn1436-4646
dc.identifier.urihttp://hdl.handle.net/11718/25894
dc.description.abstractDecision making problems are typically concerned with maximizing efficiency. In contrast, we address problems where there are multiple stakeholders and a centralized decision maker who is obliged to decide in a fair manner. Different decisions give different utility to each stakeholder. In cases where these decisions are made repeatedly, we provide efficient mathematical programming formulations to identify both the maximum fairness possible and the decisions that improve fairness over time, for reasonable metrics of fairness. We apply this framework to the problem of ambulance allocation, where decisions in consecutive rounds are constrained. With this additional complexity, we prove structural results on identifying fair feasible allocation policies and provide a hybrid algorithm with column generation and constraint programming-based solution techniques for this class of problems. Computational experiments show that our method can solve these problems orders of magnitude faster than a naive approach.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofMathematical Programmingen_US
dc.subjectfairnessen_US
dc.subjectresource allocationen_US
dc.subjecthealthcareen_US
dc.subjectdecision makingen_US
dc.subjectefficiencyen_US
dc.subjectmetrics of fairnessen_US
dc.subjectmathematical programming formulationsen_US
dc.subjectambulance allocationen_US
dc.subjecthybrid algorithmen_US
dc.subjectcolumn generationen_US
dc.subjectconstraint programmingen_US
dc.subjectcomputational experimentsen_US
dc.titleFairness over time in dynamic resource allocation with an application in healthcareen_US
dc.typeArticleen_US
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