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Representation of The Pairwise Comparisons in AHP Using Hesitant Cloud Linguistic Term Sets

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Języki publikacji
EN
Abstrakty
EN
The analytic hierarchy process (AHP) is the most popular extension to the pairwise comparisons method which is based on the observation that it is much easier to rank several objects when restricted to two objects at one time. As the pairwise comparisons are subjective, the use of linguistic expressions rather than numerical values is straightforward and friendlier due to the uncertainties that are inherent in human judgments. In this paper, to handle the uncertainty and hesitancy in practical decisionmaking situations, we represent pairwise comparisons in AHP using hesitant cloud linguistic term sets (HCLTSs) which are proposed based on hesitant fuzzy linguistic term sets (HFLTSs) and normal cloud models. Then, the synthetic cloud model aggregation algorithm is proposed to transform the HCLTS pairwise comparison matrix into the positive reciprocal synthetic cloud matrix. A prioritization method using the geometric mean technique is adopted, and the ranking method based on comparing of the parameters of normal cloud models is proposed. Thus, we extend the traditional AHP method in hesitant and uncertain environment, and we call it HCLTS-AHP method. The comparative linguistic expressions of preferences become more flexible and richer and are more similar to human beings’ cognitive models. Furthermore, the synthetic cloud model is consistent with objectivity and the calculations are easy to implement. An illustrated example is applied to the ranking of four alternatives to show the usefulness of the proposed HCLTS-AHP method.
Wydawca
Rocznik
Strony
349--362
Opis fizyczny
Bibliogr. 23 poz., tab., wykr.
Twórcy
autor
  • Department of Tourism and MICE, Chung Hua University, Hsinchu 30012, Taiwan
autor
  • Luoyang Electronic Equipment Test Center, Luoyang, He’nan 471003, China
Bibliografia
  • [1] Janicki R. Pairwise comparisons Based Non-Numerical Ranking. Fundamenta Informaticae. 2009;94(2): 197–217. doi: 10.3233/FI-2009-126.
  • [2] Saaty TL. A Scaling Method for Priorities in Hierarchical Structures. Journal of mathematical psychology. 1977;15(3):234–281. doi:10.1016/0022-2496(77)90033-5.
  • [3] Saaty T L . The Analytic Hierarchy Process. McGraw-Hill, New York; 1980. ISBN: 0070543712, 9780070543713.
  • [4] Kułakowski K. Heuristic Rating Estimation Approach to The Pairwise Comparisons Method. Fundamenta Informaticae; 2014;133(4):367–386. doi:10.3233/FI-2014-1081.
  • [5] Yang X, Zeng L, Luo F, Wang S. Cloud Hierarchical Analysis. Journal of Information & Computational Science. 2010;7(12):2468–2477.Available from: http://www.joics.com.
  • [6] Yang X, Yan L, Zeng L. How to Handle Uncertainties in AHP: The Cloud Delphi Hierarchical Analysis. Information Sciences. 2013;222:384–404. doi:10.1016/j.ins.2012.08.019
  • [7] Buckley JJ. Fuzzy Hierarchical Analysis. Fuzzy Sets And Systems. 1985;17(3):233–247. doi:10.1016/0165-0114(85)90090-9.
  • [8] Dong Y, HongWC, Xu Y, Yu S. Selecting The Individual Numerical Scale and Prioritization Method in The Analytic Hierarchy Process: A 2-Tuple Fuzzy Linguistic Approach. Fuzzy Systems, IEEE Transactions on. 2011;19(1):13–25. doi:10.1109/TFUZZ.2010.2073713.
  • [9] Li D, Han J, Shi X, Chan MC. Knowledge Representation and Discovery Based on Linguistic Atoms. Knowledge-Based Systems. 1998;10(7):431–440. Available from: http://dx.doi.org/10.1016/S0950-7051(98)00038-0.
  • [10] Li D, Liu C, Gan W. A New Cognitive Model: Cloud Model. International Journal of Intelligent Systems. 2009;24(3):357–375. doi:10.1002/int.20340.
  • [11] Li D, Du Y. Artificial Intelligence With Uncertainty. Chapman & Hall/CRC Press, Boca Raton, FL; 2007. ISBN:9781584889984.
  • [12] Yang X, Yan L, Peng H, Gao X. Encoding Words into Cloud Models From Interval-Valued Data Via Fuzzy Statistics and Membership Function Fitting. Knowledge-Based Systems. 2014;55:114–124. doi:10.1016/j.knosys.2013.10.014.
  • [13] Rodriguez RM, Martinez L, Herrera F. Hesitant Fuzzy Linguistic Term Sets for Decision Making. Fuzzy Systems, IEEE Transactions on. 2012;20(1):109–119. doi:10.1109/TFUZZ.2011.2170076.
  • [14] Torra V. Hesitant Fuzzy Sets. International Journal of Intelligent Systems. 2010;25(6):529–539. doi:10.1002/int.20418.
  • [15] Huang HC, Yang X. Pairwise Comparison and Distance Measure of Hesitant Fuzzy Linguistic Term Sets. Mathematical Problems in Engineering. 2014;2014. Available from: http://dx.doi.org/10.1155/2014/954040.
  • [16] Xu C, Wang G, Zhang Q. A New Multi-Step Backward Cloud Transformation Algorithm Based on Normal Cloud Model. Fundamenta Informaticae. 2014;133(1):55–85. doi:10.3233/FI-2014-1062.
  • [17] Li D, Cheung D, Shi X, Ng V. Uncertainty Reasoning Based on Cloud Models in Controllers. Computers & Mathematics with Applications. 1998;35(3):99–123. doi:10.1016/S0898-1221(97)00282-4.
  • [18] Li H, Guo C. Piecewise Cloud Approximation for Time Series Mining. Knowledge-Based Systems. 2011; 24(4):492–500. doi:10.1016/j.knosys.2010.12.008.
  • [19] Qin K, Xu K, Liu F, Li D. Image Segmentation Based on Histogram Analysis Utilizing The Cloud Model. Computers & Mathematics with Applications. 2011;62(7):2824–2833. doi:10.1016/j.camwa.2011.07.048.
  • [20] Zhou Z. Cognition And Removal of Impulse Noise With Uncertainty. Image Processing, IEEE Transactions on. 2012;21(7):3157–3167. doi:10.1109/TIP.2012.2189577.
  • [21] Yang XJ, Zeng L, Zhang R. Cloud Delphi Method. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 2012;20(01):77–97. doi:10.1142/S0218488512500055.
  • [22] Rodríguez RM, Martínez L, Herrera F. A Group Decision Making Model Dealing With Comparative Linguistic Expressions Based on Hesitant Fuzzy Linguistic Term Sets. Information Sciences. 2013;241:28–42. doi:10.1016/j.ins.2013.04.006.
  • [23] Wei C, Ren Z, Rodríguez RM. A Hesitant Fuzzy Linguistic TODIM Method Based on a Score Function. International Journal of Computational Intelligence Systems. 2015;8(4):701–712. doi: 10.1080/18756891. 2015.1046329.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
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