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Mean-Variance Location Problems

Author

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  • Oded Berman

    (University of Massachusetts-Harbor Campus, Boston, Massachusetts 02125)

Abstract

In this paper we discuss three mean-variance location problems. Two of them are constrained problems where one performance measure—mean of the weighted distance, or variance, is minimized subject to an upper bound constraint on the value of the other. In the third problem the objective function minimized is given by the mean plus a constant times the variance. The paper includes polynomial time algorithms to solve the three problems. The solutions produced by these algorithms are Pareto optimum solutions (solutions that are strictly better than any other solution in at least one of the two measures: mean and variance).

Suggested Citation

  • Oded Berman, 1990. "Mean-Variance Location Problems," Transportation Science, INFORMS, vol. 24(4), pages 287-293, November.
    • Handle: RePEc:inm:ortrsc:v:24:y:1990:i:4:p:287-293
    DOI: 10.1287/trsc.24.4.287
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    Cited by:

    1. Bélanger, V. & Ruiz, A. & Soriano, P., 2019. "Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles," European Journal of Operational Research, Elsevier, vol. 272(1), pages 1-23.
    2. Włodzimierz Ogryczak, 2009. "Inequality measures and equitable locations," Annals of Operations Research, Springer, vol. 167(1), pages 61-86, March.
    3. Cruz Lopez-de-los-Mozos, M. & Mesa, Juan A., 2001. "The maximum absolute deviation measure in location problems on networks," European Journal of Operational Research, Elsevier, vol. 135(1), pages 184-194, November.
    4. Drezner, Tammy & Drezner, Zvi & Hulliger, Beat, 2014. "The Quintile Share Ratio in location analysis," European Journal of Operational Research, Elsevier, vol. 238(1), pages 166-174.

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