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Recent Advances in Business Analytics. Selected papers of the 2021 KNOWCON-NSAIS workshop on Business Analytics

Annals of Computer Science and Information Systems, Volume 29

Similarity based TOPSIS with linguistic-quantifier based aggregation using OWA

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DOI: http://dx.doi.org/10.15439/2021B6

Citation: Recent Advances in Business Analytics. Selected papers of the 2021 KNOWCON-NSAIS workshop on Business Analytics, Jan Stoklasa, Pasi Luukka and Maria Ganzha (eds). ACSIS, Vol. 29, pages 45–51 ()

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Abstract. In this paper we present similarity based TOPSISwith OWA operators. The motivation behind this new method isthe fact that in many real world problems it is more importantto consider the amount of criteria that a particular alternative isable to satisfy instead of simply concentrating on the importanceof particular criteria. Here with OWA operators we can tacklethis problem together with multi-criteria decision making methodcalled TOPSIS by aggregating alternatives' similarities towardspositive ideal solution and negative ideal solution and aggregatingthese similarities using OWA. The use of linguistic quantifiersrepresented by OWA weights generated by a selected RIMquantifier allows for the reflection of decision-maker's attitude torisk in the calculation of the similarities of the alternative withpositive and negative ideal solutions.

References

  1. V. Traneva, S. Tranev, D. Mavrov, Interval-Valued Intuitionistic Fuzzy Decision-Making Method using Index Matrices and Application in Outsourcing, Annals of Computer Science and Information systems, 25, pp. 251-254, 2021, http://dx.doi.org/10.15439/2021F77
  2. A. Karczmarczyk, J. Jankowski, J. Watrobski, Multi-criteria approach to viral marketing campaign planning in social networks, based on real networks, network samples and synthetic networks, Annals of Computer Science and Inofrmation systems, 18, pp. 663-673, 2019, http://dx.doi.org/10.15439/2019F199
  3. C.L. Hwang, K. Yoon, Multiple Attributes Decision Making Methods and Applications, 1980, Springer, Berlin, Heidelberg
  4. P. Luukka, M. Collan, Histogram ranking with generalized similarity-based TOPSIS applied to patent ranking, International Journal of Operational Research 25 (4), 2016, pp. 437-448, http://dx.doi.org/10.1504/IJOR.2016.075290
  5. P. Luukka, M. Collan, Bonferroni mean based similarity based TOPSIS, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 704-709, 2016, http://dx.doi.org/10.1109/FUZZ-IEEE.2016.7737756
  6. C. Bonferroni, Sulle medie multiple di potenze, Bollettino Matematica Italiana 5, 1950, pp. 267-270.
  7. R. R. Yager, On ordered weighted averaging aggregation operators in multi-criteria decision-making, Systems, Man and Cybernetics, IEEE Transactions, Vol. 18, 1988, pp. 183-190, 1988, http://dx.doi.org/10.1109/21.87068
  8. Y. Chen, K.W. Li, S. Liu, An OWA-TOPSIS method for multiple criteria decision analysis, Expert Systems with Applications, 38, pp. 5205-5211, 2011, http://dx.doi.org/10.1016/j.eswa.2010.10.039
  9. T. Wang, J. Liu, J. Li, C. Niu, An integrating OWA-TOPSIS framework in intuitionistic fuzzy settings for multiple attribute decision making, Computers & Industrial Engineering, 98, pp. 185-194, 2016, http://dx.doi.org/10.1016/j.cie.2016.05.029
  10. F. Liu, Y-.F. Shang, L-.H. Pan, A modified TOPSIS method for obtaining the associated weights of the OWA-type operators, International journal of intelligent systems, 30, pp. 1101-1116, 2015, http://dx.doi.org/10.1002/int.21737
  11. B. Yusoff, J.M. Merigo, D.C. Hornero, Generalized OWA-TOPSIS model based on the concept of majority opinion for group decision making, FIM 2015, AISC 730, pp. 124-139, 2018.
  12. R. R. Yager, Quantifier Guided Aggregation using OWA Operators, International Journal of Intelligent Systems, Vol. 11, pp. 49-73, 1996, http://dx.doi.org/10.1002/(SICI)1098-111X(199601)11:1<49::AID-INT3>3.0.CO;2-Z
  13. Z. S. Xu, An Overview of Methods for Determining OWA Weights, International Journal of Intelligent Systems, Vol. 20, pp. 843-865, 2005, http://dx.doi.org/10.1002/int.20097