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On some convexity properties of the Least Squares Method for pairwise comparisons matrices without the reciprocity condition

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  • J. Fülöp
  • W. Koczkodaj
  • S. Szarek

Abstract

The relaxation of the reciprocity condition for pairwise comparisons is revisited from the optimization point of view. We show that some special but not extreme cases of the Least Squares Method are easy to solve as convex optimization problems after suitable nonlinear change of variables. We also give some other, less restrictive conditions under which the convexity of a modified problem can be assured, and the global optimal solution of the original problem found by using local search methods. Mathematical and psychological justifications for the relaxation of the reciprocity condition as well as numerical examples are provided. Copyright Springer Science+Business Media, LLC. 2012

Suggested Citation

  • J. Fülöp & W. Koczkodaj & S. Szarek, 2012. "On some convexity properties of the Least Squares Method for pairwise comparisons matrices without the reciprocity condition," Journal of Global Optimization, Springer, vol. 54(4), pages 689-706, December.
    • Handle: RePEc:spr:jglopt:v:54:y:2012:i:4:p:689-706
    DOI: 10.1007/s10898-011-9785-z
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    1. L Mikhailov, 2000. "A fuzzy programming method for deriving priorities in the analytic hierarchy process," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(3), pages 341-349, March.
    2. Jacinto González-Pachón & Carlos Romero, 2007. "Inferring consensus weights from pairwise comparison matrices without suitable properties," Annals of Operations Research, Springer, vol. 154(1), pages 123-132, October.
    3. Gonzalez-Pachon, Jacinto & Romero, Carlos, 2004. "A method for dealing with inconsistencies in pairwise comparisons," European Journal of Operational Research, Elsevier, vol. 158(2), pages 351-361, October.
    4. Golany, B. & Kress, M., 1993. "A multicriteria evaluation of methods for obtaining weights from ratio-scale matrices," European Journal of Operational Research, Elsevier, vol. 69(2), pages 210-220, September.
    5. Hovanov, Nikolai V. & Kolari, James W. & Sokolov, Mikhail V., 2008. "Deriving weights from general pairwise comparison matrices," Mathematical Social Sciences, Elsevier, vol. 55(2), pages 205-220, March.
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    Cited by:

    1. Pedro Linares & Sara Lumbreras & Alberto Santamaría & Andrea Veiga, 2016. "How relevant is the lack of reciprocity in pairwise comparisons? An experiment with AHP," Annals of Operations Research, Springer, vol. 245(1), pages 227-244, October.
    2. Kułakowski, Konrad & Mazurek, Jiří & Ramík, Jaroslav & Soltys, Michael, 2019. "When is the condition of order preservation met?," European Journal of Operational Research, Elsevier, vol. 277(1), pages 248-254.

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    Keywords

    Pairwise comparisons; Convexity properties;

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