Toward Computing the Margin of Victory in Single Transferable Vote Elections

Michelle Blom (), Peter J. Stuckey () and Vanessa J. Teague ()
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Michelle Blom: Department of Computing and Information Systems, The University of Melbourne, Parkville, Australia 3010
Peter J. Stuckey: Faculty of Information Technology, Monash University, Australia 3800
Vanessa J. Teague: Department of Computing and Information Systems, The University of Melbourne, Parkville, Australia 3010

INFORMS Journal on Computing, 2019, vol. 31, issue 4, 636-653

Abstract: The single transferable vote (STV) is a system of preferential voting for multiseat elections. Each ballot cast by a voter is a (potentially partial) ranking over a set of candidates. No techniques currently exist for computing the margin of victory (MOV) in STV elections. The MOV is the smallest number of ballot manipulations (changes, additions, and deletions) required to bring about a change in the set of elected candidates. Knowing the MOV gives insight into how much time and money should be spent on auditing the election, and whether uncovered mistakes (such as ballot box losses) throw the election result into doubt—requiring a costly repeat election—or can be safely ignored. We present algorithms for computing lower and upper bounds on the MOV in STV elections. In small instances, these algorithms are able to compute exact margins.

Keywords: elections; margin of victory; nonlinear mixed-integer programming; hybrid optimisation (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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