IDEAS home Printed from https://ideas.repec.org/p/urb/wpaper/08_01.html
   My bibliography  Save this paper

A generalization of Hukuhara difference for interval and fuzzy arithmetic

Author

Listed:
  • Luciano Stefanini

    (Department of Economics and Quantitative Methods, University of Urbino (Italy))

Abstract

We propose a generalization of the Hukuhara difference. First, the case of compact convex sets is examined; then, the results are applied to generalize the Hukuhara difference of fuzzy numbers, using their compact and convex level-cuts. Finally, a similar approach is seggested to attempt a generalization of division for real intervals and fuzzy numbers.

Suggested Citation

  • Luciano Stefanini, 2008. "A generalization of Hukuhara difference for interval and fuzzy arithmetic," Working Papers 0801, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2008.
    • Handle: RePEc:urb:wpaper:08_01
    as

    Download full text from publisher

    File URL: http://www.econ.uniurb.it/RePEc/urb/wpaper/WP_08_01.pdf
    File Function: First version, 2008
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luciano Stefanini & Barnab?s Bede, 2012. "Some notes on generalized Hukuhara differentiability of interval-valued functions and interval differential equations," Working Papers 1208, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2012.
    2. Beatriz Hernández-Jiménez & Gabriel Ruiz-Garzón & Antonio Beato-Moreno & Rafaela Osuna-Gómez, 2021. "A Better Approach for Solving a Fuzzy Multiobjective Programming Problem by Level Sets," Mathematics, MDPI, vol. 9(9), pages 1-14, April.
    3. Luciano Stefanini & Barnab?s Bede, 2012. "Generalized Fuzzy Differentiability with LU-parametric Representation," Working Papers 1210, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2012.
    4. Sankar Prasad Mondal & Tapan Kumar Roy, 2017. "Solution of second order linear fuzzy ordinary differential equation by Lagrange multiplier method with application in mechanics," OPSEARCH, Springer;Operational Research Society of India, vol. 54(4), pages 766-798, December.
    5. Saed Mallak & Doa’a Farekh & Basem Attili, 2021. "Numerical Investigation of Fuzzy Predator-Prey Model with a Functional Response of the Form Arctan ( ax )," Mathematics, MDPI, vol. 9(16), pages 1-22, August.
    6. Luciano Stefanini & Barnabas Bede, 2008. "Generalized Hukuhara Differentiability of Interval-valued Functions and Interval Differential Equations," Working Papers 0803, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2008.
    7. Yating Guo & Guoju Ye & Wei Liu & Dafang Zhao & Savin Treanţǎ, 2021. "Optimality Conditions and Duality for a Class of Generalized Convex Interval-Valued Optimization Problems," Mathematics, MDPI, vol. 9(22), pages 1-14, November.
    8. Jules Sadefo Kamdem & Babel Raïssa Guemdjo Kamdem & Carlos Ougouyandjou, 2021. "S-ARMA Model and Wold Decomposition for Covariance Stationary Interval-Valued Time Series Processes," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 191-213, March.
    9. Majumder, Pinki & Mondal, Sankar Prasad & Bera, Uttam Kumar & Maiti, Manoranjan, 2016. "Application of Generalized Hukuhara derivative approach in an economic production quantity model with partial trade credit policy under fuzzy environment," Operations Research Perspectives, Elsevier, vol. 3(C), pages 77-91.
    10. Barnab?s Bede & Luciano Stefanini, 2012. "Generalized Differentiability of Fuzzy-valued Functions," Working Papers 1209, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2012.
    11. Zhang, Qinchunxue & Shu, Lan & Jiang, Bichuan, 2023. "Moran process in evolutionary game dynamics with interval payoffs and its application," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    12. Sadefo Kamdem, J. & Mbairadjim Moussa, A. & Terraza, M., 2012. "Fuzzy risk adjusted performance measures: Application to hedge funds," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 702-712.
    13. Qingsong Mao & Huan Huang, 2021. "Interval Ranges of Fuzzy Sets Induced by Arithmetic Operations Using Gradual Numbers," Mathematics, MDPI, vol. 9(12), pages 1-15, June.
    14. R. Sujatha & T. M. Rajalaxmi, 2016. "Hierarchical Fuzzy Hidden Markov Chain for Web Applications," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(01), pages 83-118, January.
    15. Fanyong Meng & Xiaohong Chen & Chunqiao Tan, 2016. "Cooperative fuzzy games with interval characteristic functions," Operational Research, Springer, vol. 16(1), pages 1-24, April.
    16. Regivan Santiago & Flaulles Bergamaschi & Humberto Bustince & Graçaliz Dimuro & Tiago Asmus & José Antonio Sanz, 2020. "On the Normalization of Interval Data," Mathematics, MDPI, vol. 8(11), pages 1-18, November.
    17. Debdas Ghosh, 2016. "A Newton method for capturing efficient solutions of interval optimization problems," OPSEARCH, Springer;Operational Research Society of India, vol. 53(3), pages 648-665, September.

    More about this item

    Keywords

    Fuzzy Arithmetic; Interval Arithmetic; Hukuhara difference; Fuzzy Numbers.;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:urb:wpaper:08_01. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Carmela Nicoletti (email available below). General contact details of provider: https://edirc.repec.org/data/feurbit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.