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Standard sensitivity analysis and additive tolerance approach in MOLP

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Abstract

We consider sensitivity analysis of the objective function coefficients in multiple objective linear programming (MOLP). We focus on the properties of the parameters set for which a given extreme solution is efficient. Moreover, we compare two approaches: the standard sensitivity analysis (changing only one coefficient) and the additive tolerance approach (changing all coefficients). We find the connections between these two approaches by giving a theorem describing the upper bound on the maximal additive tolerance.

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References

  • Benson, H. P., & Sun, E. (2002). A weight set decomposition algorithm for finding all efficient extreme points in the outcome set of a multiple objective linear program. European Journal of Operational Research, 139(1), 26–41.

    Article  Google Scholar 

  • Borges, A. R., & Antunes, C. H. (2002). A visual interactive tolerance approach to sensitivity analysis in MOLP. European Journal of Operational Research, 142(2), 357–381.

    Article  Google Scholar 

  • Dauer, J., & Liu, Y. H. (1997). Multiple-criteria and goal programming. In T. Gal & H. J. Greenberg (Eds.), Advances in sensitivity analysis and parametric programming. Boston: Kluwer Academic. Section 11.

    Google Scholar 

  • Gal, T. (1997). A historical sketch on sensitivity analysis and parametric programming. In T. Gal & H. J. Greenberg (Eds.), Advances in sensitivity analysis and parametric programming. Boston: Kluwer Academic.

    Google Scholar 

  • Gal, T., & Wolf, K. (1986). Stability in vector maximization—a survey. European Journal of Operational Research, 25, 169–182.

    Article  Google Scholar 

  • Hansen, P., Labbe, M., & Wendell, R. E. (1989). Sensitivity analysis in multiple objective linear programming: the tolerance approach. European Journal of Operational Research, 38, 63–69.

    Article  Google Scholar 

  • Hladik, M. (2008). Additive and multiplicative tolerance in multiobjective linear programming. Operations Research Letters, 36, 393–396.

    Article  Google Scholar 

  • Oliveira, C., & Antunes, C. H. (2007). Multiple objective linear programming models with interval coefficients—an illustrated overview. European Journal of Operational Research, 181(3), 1434–1463.

    Article  Google Scholar 

  • Sitarz, S. (2008). Postoptimal analysis in multicriteria linear programming. European Journal of Operational Research, 191, 7–18.

    Article  Google Scholar 

  • Steuer, R. (1986). Multiple criteria optimization theory: computation and application. New York: Willey.

    Google Scholar 

  • Wendell, R. E. (1982). A preview of a tolerance approach to sensitivity analysis in linear programming. Discrete Mathematics, 38, 121–124.

    Article  Google Scholar 

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Correspondence to Sebastian Sitarz.

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Sitarz, S. Standard sensitivity analysis and additive tolerance approach in MOLP. Ann Oper Res 181, 219–232 (2010). https://doi.org/10.1007/s10479-010-0728-8

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  • DOI: https://doi.org/10.1007/s10479-010-0728-8

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