Abstract

Providing equal access to public service resources is a fundamental goal of democratic societies. Growing research interest in public services (e.g., health care, humanitarian relief, elections) has increased the importance of considering objective functions related to equity. This article studies discrete resource allocation problems where the decision maker is concerned with maintaining equity between some defined subgroups of a customer population and where non-closed-form functions of equity are allowed. Simulation optimization techniques are used to develop rigorous algorithms to allocate resources equitably among these subgroups. The presented solutions are associated with probabilistic bounds on solution quality. A full-factorial experimental design demonstrates that the proposed algorithm outperforms competing heuristics and is robust over various inequity metrics. Additionally, the algorithm is applied to a case study of allocating voting machines to election precincts in Franklin County, Ohio. [Supplementary material is available for this article. Go to the publisher’s online edition of IIE Transactions for the Appendices to the article.]

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