Fair Resource Allocation by Gini Index Minimization

Wlodzimierz Ogryczak () and Grzegorz Zalewski
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Wlodzimierz Ogryczak: Warsaw University of Technology
Grzegorz Zalewski: National Institute of Telecommunications

A chapter in Operations Research Proceedings 2018, 2019, pp 77-83 from Springer

Abstract: Abstract In many resource allocation problems there is a need to minimize inequity to respect some fairness rules while looking for the overall efficiency. The Gini index representing the relative mean absolute difference of outcomes is the classical measure of inequity in outcome distribution. It was empirically found in real-life applications that the Gini index minimization while equalizing the outcomes it may simultaneously support their maximization (allocation efficiency). However, it depends on the feasible set structure and there is no guarantee to achieve good equitable and efficient allocation scheme. We show that with appropriate outcome shift the Gini index minimization is consistent both with inequity minimization and with outcomes maximization thus guaranteeing equitable allocation schemes. The interval of appropriate target values depends on the problem structure (feasible set). Although it can be found or adjusted during the optimization process without necessity of a special feasible set analysis.

Keywords: Multi-objective programming; Decision theory and analysis; Fairness; Equity; Efficiency; OR/MS and the public sector (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-030-18500-8_11

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DOI: 10.1007/978-3-030-18500-8_11

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