Efficiency and equity tradeoffs in voting machine allocation problems
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Efficiency and equity are the two crucial factors to be considered when allocating public resources such as voting machines. Existing allocation models are all single-objective, focusing on maximizing either efficiency or equity despite the fact that the actual decision-making process involves both issues simultaneously. We propose a bi-objective integer program to analyse the tradeoff between the two competing objectives. The new model quantifies the sacrifice in efficiency in order to achieve a certain improvement in equity and vice versa. Using data from the 2008 United States Presidential election in Franklin County, Ohio, we demonstrate that our model is capable of producing significantly more balanced allocation plans, in terms of efficiency and equity, than current practice or other competing methods.
Keywordsefficiency-equity tradeoff efficient allocation voting operations public service
- Allen TT (2013). Delving into the reasons for long lines can bring solutions. Orlando Sentinel, 8 January, http://articles.orlandosentinel.com/2013-01-08/news/os-ed-long-lines-voting-florida-010813-20130107_1_long-lines-ballot-length-turnout, accessed 30 october 2013.
- Allen TT and Bernshteyn MB (2006b). Optimal voting machine allocation analysis. In: Hertzberg S (ed). Analysis of May 2006 Primary Cuyahoga County. Election Science Institute: Ohio, pp 71–89.Google Scholar
- Belenky AS and Larson RC (2008). To queue or not to queue? Analytics. Spring: 22–26.Google Scholar
- Cohon JL (1978). Multiobjective Programming and Planning. Academic Press: New York.Google Scholar
- Edelstein WA and Edelstein AD (2010). Queuing and elections: Long lines, DREs and paper ballots. Proceedings of the 2010 Electronic Voting Technology Workshop/Workshop on Trustworthy Elections, Washington, DC.Google Scholar
- Ehrgott M and Gandibleux X (2002). Multiple Criteria Optimization: State of the Art Annotated Bibliographic Surveys. Springer: Norwell, MA.Google Scholar
- Feldman D and Belcher C (2005). Voting experience survey. Democracy at risk: The 2004 election in Ohio. Democratic National Committee. http://a9.g.akamai.net/7/9/8082/v001/www.democrats.org/pdfs/ohvrireport/section03.pdf, accessed 15 March 2013.
- Fessler P (2012). Fixing long election lines may be easier said than done. http://www.npr.org/blogs/itsallpolitics/2012/11/08/164651410/fixing-long-election-lines-may-be-easier-said-than-done, accessed 15 March 2013.
- Levine A (2008). Excitement, frustration as early voters brave long lines. http://www.cnn.com/2008/POLITICS/11/02/early.voting/index.html, accessed 15 March 2013.
- McDonald M (2012). The United States Elections Project, http://elections.gmu.edu/voter_turnout.html, accessed 31 October 2013.Google Scholar
- Mebane WR (2006). Voting machine allocation in Franklin County, Ohio, 2004: Response to U.S. Department of Justice Letter of June 29, 2005. http://www-personal.umich.edu/~wmebane/franklin2.pdf, accessed 6 November 2013.
- Miettinen KM (1999). Nonlinear Multiobjective Optimization. Kluwer Academic: Norwell, MA.Google Scholar
- Mulligan GF (1991). Equality measures and facility location. Regional Science 7 (4): 548–561.Google Scholar
- Ripley A (2008). Secrets of What Makes Your Polling Place Work—Or Not. Time, 3 November, http://content.time.com/time/politics/article/0,8599,1855861,00.html, accessed 30 October 2013.
- Smith M (2012). Long lines but few snags in U.S. election. CNN, 6 November, http://www.cnn.com/2012/11/06/politics/election-voting/index.html, accessed 15 March 2013.
- Steuer RE (1986). Multiple Criteria Optimization, Theory, Computation and Application. Wiley: New York.Google Scholar
- Ulungu L and Teghem J (1995). The two phase method: An efficient procedure to solve bi-objective combinatorial optimization problems. Foundations of Computing and Decision Sciences 20 (2): 149–165.Google Scholar