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Bireference Procedure fBIP for Interactive Multicriteria Optimization with Fuzzy Coefficients

Author

Listed:
  • Piotr Wojewnik

    (Warsaw School of Economics)

  • Tomasz Szapiro

    (Warsaw School of Economics)

Abstract

In the paper an approach to decision making in situations with non-pointlike characterisation and subjective evaluation of the actions is considered. The decision situation is represented mathematically as fuzzy multiobjective linear programming (fMOLP) model, where we apply the reduced fuzzy matrices instead of fuzzy classical numbers. The fMOLP model with reduced parameters is decomposable into the set of point-like models and the point-like models enable effective construction of an optimisation procedure - fBIP, see Wojewnik (2006ab), extending the bireference procedure by Michalowski and Szapiro (1992). The approach is applied to a fuzzy optimization problem in the area of telecommunication services.

Suggested Citation

  • Piotr Wojewnik & Tomasz Szapiro, 2010. "Bireference Procedure fBIP for Interactive Multicriteria Optimization with Fuzzy Coefficients," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 2(3), pages 169-193, June.
    • Handle: RePEc:psc:journl:v:2:y:2010:i:3:p:169-193
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    References listed on IDEAS

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    1. Ignacy Kaliszewski, 2006. "Soft Computing For Complex Multiple Criteria Decision Making," International Series in Operations Research and Management Science, Springer, number 978-0-387-30177-8, September.
    2. Kaliszewski, Ignacy, 2004. "Out of the mist--towards decision-maker-friendly multiple criteria decision making support," European Journal of Operational Research, Elsevier, vol. 158(2), pages 293-307, October.
    3. Wojtek Michalowski & Tomek Szapiro, 1992. "A Bi-Reference Procedure for Interactive Multiple Criteria Programming," Operations Research, INFORMS, vol. 40(2), pages 247-258, April.
    4. Rommelfanger, Heinrich, 1989. "Interactive decision making in fuzzy linear optimization problems," European Journal of Operational Research, Elsevier, vol. 41(2), pages 210-217, July.
    5. Mohan, C. & Nguyen, H. T., 1998. "Reference direction interactive method for solving multiobjective fuzzy programming problems," European Journal of Operational Research, Elsevier, vol. 107(3), pages 599-613, June.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Stanley Zionts & Jyrki Wallenius, 1983. "An Interactive Multiple Objective Linear Programming Method for a Class of Underlying Nonlinear Utility Functions," Management Science, INFORMS, vol. 29(5), pages 519-529, May.
    8. Jaszkiewicz, Andrzej & Slowinski, Roman, 1999. "The `Light Beam Search' approach - an overview of methodology and applications," European Journal of Operational Research, Elsevier, vol. 113(2), pages 300-314, March.
    9. Luque, Mariano & Ruiz, Francisco & Steuer, Ralph E., 2010. "Modified interactive Chebyshev algorithm (MICA) for convex multiobjective programming," European Journal of Operational Research, Elsevier, vol. 204(3), pages 557-564, August.
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    Cited by:

    1. Tadeusz Trzaskalik, 2022. "Multiobjective dynamic programming in bipolar multistage method," Annals of Operations Research, Springer, vol. 311(2), pages 1259-1279, April.
    2. Tadeusz Trzaskalik, 2023. "Vectors of indicators and pointer function in the Multistage Bipolar Method," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(3), pages 791-816, September.

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    More about this item

    Keywords

    decision support; multicriteria decision making; interactive optimization; fuzzy optimization;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications

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