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The U.S. Navy explores detailing cost reduction via Data Envelopment Analysis

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  • Sutton, Warren
  • Dimitrov, Stanko

Abstract

In this paper we show how a variation of Data Envelopment Analysis, the Generalized Symmetric Weight Assignment Technique, is used to assign sailors to jobs for the U.S. Navy. This method differs from others as the assignment is a multi-objective problem where the importance of each objective, called a metric, is determined by the decision-maker and promoted within the assignment problem. We explore how the method performs as the importance of particular metrics increases. Finally, we show that the proposed method leads to substantial cost savings for the U.S. Navy without degrading the resulting assignments’ performance on other metrics.

Suggested Citation

  • Sutton, Warren & Dimitrov, Stanko, 2013. "The U.S. Navy explores detailing cost reduction via Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 227(1), pages 166-173.
    • Handle: RePEc:eee:ejores:v:227:y:2013:i:1:p:166-173
    DOI: 10.1016/j.ejor.2012.11.058
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    References listed on IDEAS

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    1. Dimitrov, Stanko & Sutton, Warren, 2013. "Generalized symmetric weight assignment technique: Incorporating managerial preferences in data envelopment analysis using a penalty function," Omega, Elsevier, vol. 41(1), pages 48-54.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. Dan Shrimpton & Alexandra M. Newman, 2005. "The US Army Uses a Network Optimization Model to Designate Career Fields for Officers," Interfaces, INFORMS, vol. 35(3), pages 230-237, June.
    4. Dan O. Bausch & Gerald G. Brown & Danny R. Hundley & Stephen H. Rapp & Richard E. Rosenthal, 1991. "Mobilizing Marine Corps Officers," Interfaces, INFORMS, vol. 21(4), pages 26-38, August.
    5. Pentico, David W., 2007. "Assignment problems: A golden anniversary survey," European Journal of Operational Research, Elsevier, vol. 176(2), pages 774-793, January.
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