IDEAS home Printed from https://ideas.repec.org/a/cbu/jrnlec/y2014vspecialp204-209.html
   My bibliography  Save this article

Grey Relational Analysis Method For Intuitionistic Fuzzy Multiple Attribute Decision Making

Author

Listed:
  • IULIANA CARMEN BARBACIORU

    (”CONSTANTIN BRANCUSI” UNIVERSITY OF TARGU JIU)

Abstract

Grey system theory is one of the methods used to study uncertainty. GRA is part of grey system theory, which is suitable for solving problems with complicated interrelationships between multiple factors and variables. This method has been widely used to solve the uncertainty problems under the discrete data and incomplete information. It is one of the best methods to make decisions under business environment. In the process of intuitionistic fuzzy multiple attribute decision making (MADM) problems, the information about attribute weights and the attribute values is incompletely known because of time pressure, lack of knowledge or data, and the expert’s limited expertise about the problem domain. The aim of this paper is to develop a new method, based on the traditional GRA method, to overcome this limitation. In this sense, you use a different distance between two intuitionistic fuzzy numbers. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Suggested Citation

  • Iuliana Carmen Barbacioru, 2014. "Grey Relational Analysis Method For Intuitionistic Fuzzy Multiple Attribute Decision Making," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 0, pages 204-209, May.
  • Handle: RePEc:cbu:jrnlec:y:2014:v:special:p:204-209
    as

    Download full text from publisher

    File URL: http://www.utgjiu.ro/revista/ec/pdf/2014-04.Special/36_Barbacioru%202.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kim, Soung Hie & Ahn, Byeong Seok, 1999. "Interactive group decision making procedure under incomplete information," European Journal of Operational Research, Elsevier, vol. 116(3), pages 498-507, August.
    2. Kim, Soung Hie & Choi, Sang Hyun & Kim, Jae Kyeong, 1999. "An interactive procedure for multiple attribute group decision making with incomplete information: Range-based approach," European Journal of Operational Research, Elsevier, vol. 118(1), pages 139-152, October.
    3. Park, Kyung Sam & Kim, Soung Hie, 1997. "Tools for interactive multiattribute decisionmaking with incompletely identified information," European Journal of Operational Research, Elsevier, vol. 98(1), pages 111-123, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. S H Choi & B S Ahn, 2009. "IP-MAGS: an incomplete preference-based multiple attribute group support system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(4), pages 496-505, April.
    2. Han, Chang Hee & Kim, Jae Kyeong & Choi, Sang Hyun, 2004. "Prioritizing engineering characteristics in quality function deployment with incomplete information: A linear partial ordering approach," International Journal of Production Economics, Elsevier, vol. 91(3), pages 235-249, October.
    3. Ni Li & Minghui Sun & Zhuming Bi & Zeya Su & Chao Wang, 2014. "A new methodology to support group decision-making for IoT-based emergency response systems," Information Systems Frontiers, Springer, vol. 16(5), pages 953-977, November.
    4. Dias, Luis C. & Climaco, Joao N., 2005. "Dealing with imprecise information in group multicriteria decisions: a methodology and a GDSS architecture," European Journal of Operational Research, Elsevier, vol. 160(2), pages 291-307, January.
    5. Mateos, A. & Jimenez, A. & Rios-Insua, S., 2006. "Monte Carlo simulation techniques for group decision making with incomplete information," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1842-1864, November.
    6. Fu, Chao & Yang, Shanlin, 2012. "An evidential reasoning based consensus model for multiple attribute group decision analysis problems with interval-valued group consensus requirements," European Journal of Operational Research, Elsevier, vol. 223(1), pages 167-176.
    7. G Özerol & E Karasakal, 2008. "Interactive outranking approaches for multicriteria decision-making problems with imprecise information," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1253-1268, September.
    8. Zeshui Xu, 2006. "A Note on Linguistic Hybrid Arithmetic Averaging Operator in Multiple Attribute Group Decision Making with Linguistic Information," Group Decision and Negotiation, Springer, vol. 15(6), pages 593-604, November.
    9. C H Han & B S Ahn, 2005. "Interactive group decision-making procedure using weak strength of preference," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(10), pages 1204-1212, October.
    10. Xiaoyue Liu & Dawei Ju, 2021. "Hesitant Fuzzy 2-Dimension Linguistic Programming Technique for Multidimensional Analysis of Preference for Multicriteria Group Decision Making," Mathematics, MDPI, vol. 9(24), pages 1-23, December.
    11. Mustajoki, Jyri & Hamalainen, Raimo P. & Lindstedt, Mats R.K., 2006. "Using intervals for global sensitivity and worst-case analyses in multiattribute value trees," European Journal of Operational Research, Elsevier, vol. 174(1), pages 278-292, October.
    12. Madjid Tavana & Mariya Sodenkamp & Leena Suhl, 2010. "A soft multi-criteria decision analysis model with application to the European Union enlargement," Annals of Operations Research, Springer, vol. 181(1), pages 393-421, December.
    13. Qiang Yang & Ping-an Du & Yong Wang & Bin Liang, 2018. "Developing a rough set based approach for group decision making based on determining weights of decision makers with interval numbers," Operational Research, Springer, vol. 18(3), pages 757-779, October.
    14. M Tavana & M A Sodenkamp, 2010. "A fuzzy multi-criteria decision analysis model for advanced technology assessment at Kennedy Space Center," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(10), pages 1459-1470, October.
    15. Luis V. Montiel & J. Eric Bickel, 2014. "A Generalized Sampling Approach for Multilinear Utility Functions Given Partial Preference Information," Decision Analysis, INFORMS, vol. 11(3), pages 147-170, September.
    16. Kim, Soung Hie & Han, Chang Hee, 2000. "Establishing dominance between alternatives with incomplete information in a hierarchically structured attribute tree," European Journal of Operational Research, Elsevier, vol. 122(1), pages 79-90, April.
    17. Xiaoyang Zhou & Yan Tu & Jing Han & Jiuping Xu & Xionghui Ye, 2017. "A Class of Level-2 Fuzzy Decision-Making Model with Expected Objectives and Chance Constraints: Application to Supply Chain Network Design," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 907-938, July.
    18. Zhang, Hengjie & Dong, Yucheng & Chiclana, Francisco & Yu, Shui, 2019. "Consensus efficiency in group decision making: A comprehensive comparative study and its optimal design," European Journal of Operational Research, Elsevier, vol. 275(2), pages 580-598.
    19. Angilella, Silvia & Greco, Salvatore & Matarazzo, Benedetto, 2010. "Non-additive robust ordinal regression: A multiple criteria decision model based on the Choquet integral," European Journal of Operational Research, Elsevier, vol. 201(1), pages 277-288, February.
    20. Liesio, Juuso & Mild, Pekka & Salo, Ahti, 2007. "Preference programming for robust portfolio modeling and project selection," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1488-1505, September.

    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:cbu:jrnlec:y:2014:v:special:p:204-209. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Ecobici Nicolae (email available below). General contact details of provider: https://edirc.repec.org/data/fetgjro.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.