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dc.contributor.advisorKarsu, Özlem
dc.contributor.authorYavuz, Mirel
dc.date.accessioned2018-06-05T09:09:20Z
dc.date.available2018-06-05T09:09:20Z
dc.date.copyright2018-05
dc.date.issued2018-06
dc.date.submitted2018-06-04
dc.identifier.urihttp://hdl.handle.net/11693/46987
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.): Bilkent University, Department of Industrial Engineering, İhsan Doğramacı Bilkent University, 2018.en_US
dc.descriptionIncludes bibliographical references (leaves 53-54).en_US
dc.description.abstractFairness has become one of the primary concerns in several Operational Research (OR) problems, especially in resource allocation problems. It is crucial to ensure a fair distribution of the resources across the entities so that the proposed solutions will be both applicable and acceptable. In many real-life systems, the most e cient solution will not be the most fair solution, which creates a trade-o between e ciency and fairness. We propose two approaches in order to help the decision makers (DM) to nd an e cient solution which take fairness of the distribution of resources into account. First approach we propose is optimizing a speci c subset of the set of Schur-concave functions, namely ordered weighted averaging (OWA) functions, which are able to re ect both e ciency and fairness concerns. We do not assume that the weights of the DM to be used in OWA functions are readily available. We explore a wide range of weight vectors and report results for these di erent choices of weights. We illustrate the approach using a workload allocation problem and a knapsack problem and visualize the trade-o between fairness and e ciency. In some applications, the DM may provide a reference point such that the aim would be nding an e cient solution which is more preferable than this reference in terms of fairness. For such cases we propose a second approach that maximizes e ciency while controlling fairness concerns via a constraint. Similar to the rst approach, fairness concerns are re ected using OWA function forms. However, the resulting formulation yields to non-linearity. Thus, a hybrid interactive algorithm is presented that tackles this nonlinearity using an enumerative approach. The algorithm nds an e cient solution which OWA dominates the reference point by interacting with the DM. The algorithm is tested on knapsack problems and shows successful performance.en_US
dc.description.statementofresponsibilityby Mirel Yavuz.en_US
dc.format.extentix, 60 leaves : charts ; 30 cmen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectResource Allocation Problemen_US
dc.subjectFairnessen_US
dc.subjectKnapsack Problemen_US
dc.subjectInteractive Algorithmen_US
dc.subjectOrdered Weighted Averagingen_US
dc.titleTwo approaches for fair resource allocationen_US
dc.title.alternativeEşitlikçi kaynak dağıtımına iki yaklaşımen_US
dc.typeThesisen_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US
dc.identifier.itemidB158449


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