A novel CE-PT-MABAC method for T-spherical uncertain linguistic multiple attribute group decision-making

Complex & Intelligent Systems - Trang 1-32 - 2024
Haolun Wang1, Liangqing Feng1, Kifayat Ullah2, Harish Garg3
1School of Economics and Management, Nanchang Hangkong University, Nanchang, China
2Department of Mathematics, Riphah International University (Lahore Campus), Lahore, Pakistan
3Department of Mathematics, Thapar Institute of Engineering and Technology (Deemed University), Patiala, India

Tóm tắt

A T-spherical uncertain linguistic set (TSULS) is not only an expanded form of the T-spherical fuzzy set and the uncertain linguistic set but can also integrate the quantitative judging ideas and qualitative assessing information of decision-makers. For the description of complex and uncertain assessment data, TSULS is a powerful tool for the precise description and reliable processing of information data. However, the existing multi-attribute border approximation area comparison (MABAC) method has not been studied in TSULS. Thus, the goal of this paper is to extend and improve the MABAC method to tackle group decision-making problems with completely unknown weight information in the TSUL context. First, the cross-entropy measure and the interactive operation laws for the TSUL numbers are defined, respectively. Then, the two interactive aggregation operators for TSUL numbers are developed, namely T-spherical uncertain linguistic interactive weighted averaging and T-spherical uncertain linguistic interactive weighted geometric operators. Their effective properties and some special cases are also investigated. Subsequently, a new TSULMAGDM model considering the DM’s behavioral preference and psychology is built by integrating the interactive aggregation operators, the cross-entropy measure, prospect theory, and the MABAC method. To explore the effectiveness and practicability of the proposed model, an illustrative example of Sustainable Waste Clothing Recycling Partner selection is presented, and the results show that the optimal solution is h3. Finally, the reliable, valid, and generalized nature of the method is further verified through sensitivity analysis and comparative studies with existing methods.

Tài liệu tham khảo

Chen SM, Hong JA (2014) Fuzzy multiple attributes group decision making based on ranking interval type-2 fuzzy sets and the TOPSIS method. IEEE Trans Syst Man CybernSyst 44(12):1665–1673 Ju YB, Liu XY, Wang AH (2016) Some new Shapley 2-tuple linguistic Choquet aggregation operators and their applications to multiple attribute group decision making. Soft Comput 20:4037–4053 Herrera F, Herrera-Viedma E, Verdegay JL (1996) A model of consensus in group decision making under linguistic assessment. Fuzzy Sets Syst 78(1):73–87 Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning. Inf Sci 8(3):199–249 Rodriguez RM, Martinez L, Herrera F (2012) Hesitant fuzzy linguistic term sets for decision making. IEEE Trans Fuzzy Syst 20(1):109–119 Liu PD (2013) Some generalized dependent aggregation operators with intuitionistic linguistic numbers and their application to group decision making. J Comput Syst Sci 79(1):131–143 Herrera F, Martinez L (2000) A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Trans Fuzzy Syst 8(6):746–752 Xu ZS (2004) Uncertain linguistic aggregation operators based approach to multiple attribute group decision making under uncertain linguistic environment. Inf Sci 168(1–4):171–184 Liu PD, Jin F (2012) Methods for aggregating intuitionistic uncertain linguistic variables and their application to group decision making. Inf Sci 205:58–71 Liu PD, Liu ZM, Zhang X (2014) Some intuitionistic uncertain linguistic Heronian mean operators and their application to group decision making. Appl Math Comput 230:570–586 Liu ZM, Liu PD (2017) Intuitionistic uncertain linguistic partitioned Bonferroni means and their application to multiple decision-making. Int J SystSci 48(5):1092–1105 Liu PD, Zhang XH (2019) Some intuitionistic uncertain linguistic Bonferroni mean operators and their application to group decision. Soft Comput 23:3869–3886 Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96 Liu ZM, Liu PD, Liu WL, Pang JY (2017) Pythagorean uncertain linguistic partitioned Bonferroni mean operators and their application in multi-attribute decision making. J Intell Fuzzy Syst 32(3):2779–2790 Geng Y, Liu PD, Teng F, Liu Z (2017) Pythagorean fuzzy uncertain linguistic TODIM method and their application to multiple criteria group decision making. J Intell Fuzzy Syst 33(6):3383–3395 Lu M, Wei GW (2017) Pythagorean uncertain linguistic aggregation operators for multiple attribute decision making. Int J Knowl-Based In 21(3):165–179 Liu HC, Ding XF (2019) A new approach for emergency decision-making based on zero sum game with Pythagorean fuzzy uncertain linguistic variables. Int J Fuzzy Syst 34(7):1667–1684 Wang HD, He SF, Li CD (2019) Pythagorean uncertain linguistic variable Hamy mean operator and its application to multi-attribute group decision making. IEEE-CAA J Autom 6(2):527–539 Yager RR, Abbasov AM (2013) Pythagorean membership grades, complex numbers, and decision making. Int J Intell Syst 28(5):436–452 Bai KY, Zhu XM, Wang J, Zhang RT (2020) Power partitioned Heronian mean operators for q-rung orthopair uncertain linguistic sets with their application to multi-attribute group decision making. Int J Intell Syst 35:3–37 Xing YP, Zhang RT, Zhu XM, Bai KY (2019) q-Rung orthopair fuzzy uncertain linguistic choquet integral operators and their application to multi-attribute decision making. J Intell Fuzzy Syst 37:1123–1139 Liu ZM, Li L, Li JQ (2019) q-Rung orthopair uncertain linguistic partitioned Bonferroni mean operators and its application to multiple attribute decision-making method. Int J Intell Syst 34:2490–2520 Yang Z, Garg H (2022) Interaction power partitioned Maclaurin Symmetric mean operators under q-rung orthopair uncertain linguistic information. Int J Fuzzy Syst 24(2):1079–1097 Liu ZM, Xu HX, Yu YN, Li JQ (2019) Someq-rung orthopair uncertain linguistic aggregation operators and their application to multiple attribute group decision making. Int J Intell Syst 34(10):2521–2555 Wang J, Zhang RT, Li L, Zhu XM, Shang XP (2019) A novel approach to multi-attribute group decision making based on q-rung orthopair uncertain linguistic information. J Intell Fuzzy Syst 36(6):5565–5581 Yager RR (2017) Generalized orthopair fuzzy sets. IEEE T Fuzzy Syst 25:1222–1230 Cuong BC (2014) Picture fuzzy sets. J Comput Sci Cyber 30(4):409–420 Ganie AH, Singh S, Bhatia PK (2020) Some new correlation coefficients of picture fuzzy sets with applications. Neural Comput Appl 32:12609–12625 Luo MX, Zhang Y (2020) A new similarity measure between picture fuzzy sets and its application. Eng Appl Artif Intel 96:103956 Wei GW (2017) Picture uncertain linguistic Bonferroni mean operators and their application to multiple attribute decision making. Kybernetes 46(10):1777–1800 Naeem M, Qiyas M, Abdullah S (2021) An approach of interval-valued picture fuzzy uncertain linguistic aggregation operator and their application on supplier selection decision-making in logistics service value concretion. Math Probl Eng 2021:8873230 Garg H, Ali Z, Mahmood T (2021) Interval-valued picture uncertain linguistic generalized Hamacher aggregation operators and their application in multiple attribute decision-making process. Arab J Sci Eng 46:10153–10170 Mahmood T, Ullah K, Khan Q, Jan N (2019) An approach toward decision-making and medical diagnosis problems using the concept of spherical fuzzy sets. Neural Comput Appl 31(11):7041–7053 Ullah K, Ali Z, Mahmood T, Garg H, Chinram R (2022) Methods for multi-attribute decision making, pattern recognition and clustering based on T-spherical fuzzy information measures. J Intell Fuzzy Syst 42(4):2957–2977 Wu MQ, Chen TY, Fan JP (2020) Divergence measure of T-spherical fuzzy sets and its applications in pattern recognition. IEEE Access 8:10208–10221 Ullah K, Mahmood T, Garg H (2020) Evaluation of the performance of search and rescue robots using T-spherical fuzzy Hamacher aggregation operators. Int J Fuzzy Syst 22(2):570–582 Mahmood T, Warraich MS, Ali Z, Pamucar D (2021) Generalized MULTIMOORA method and Dombi prioritized weighted aggregation operators based on T-spherical fuzzy sets and their applications. Int J Intell Syst 36(9):4659–4692 Ju YB, Liang YY, Luo C, Dong PW, Gonzalez EDRS, Wang AH (2021) T-spherical fuzzy TODIM method for multi-criteria group decision-making problem with incomplete weight information. Soft Comput 25:2981–3001 Wang HL, Zhang FM (2022) Interaction power Heronian mean aggregation operators for multiple attribute decision making with T-spherical fuzzy information. J Intell Fuzzy Sys 42(6):5715–5739 Liu PD, Khan Q, Mahmood T, Hassan N (2019) T-spherical fuzzy power Muirhead mean operator based on novel operational laws and their application in multi-attribute group decision making. IEEE Access 7:22613–22632 Garg H, Ullah K, Mahmood T, Hassan N, Jan N (2021) T-spherical fuzzy power aggregation operators and their applications in multi-attribute decision making. J Amb Intell Hum Comput 12:9067–9080 Mahnaz S, Ali J, Malik MGA, Bashir Z (2022) T-spherical fuzzy Frank aggregation operators and their application to decision making with unknown weight information. IEEE Access 10:7408–7438 Wang JC, Chen TY (2021) A T-spherical fuzzy ELECTRE approach for multiple criteria assessment problem from a comparative perspective of score functions. J Intell Fuzzy Syst 41(2):3751–3770 Yang W, Pang YF (2022) T-spherical fuzzy ORESTE method based on cross-entropy measures and its application in multiple attribute decision-making. Soft Comput 26(19):10371–10387 Fan JP, Han DS, Wu MQ (2022) T-spherical fuzzy COPRAS method for multi-criteria decision-making problem J. Intell Fuzzy Syst 43(3):2789–2801 Wang HL, Mahmood T, Ullah K (2023) Improved CoCoSo method based on Frank softmax aggregation operators for T-spherical fuzzy multiple attribute group decision-making. Int J Fuzzy Syst 25(3):1275–1310 Wang HL, Ullah K (2023) T-spherical uncertain linguistic MARCOS method based on generalized distance and Heronian mean for multi-attribute group decision-making with unknown weight information. Complex Intell Syst 9(2):1837–1869 Pamucar D, Cirovic G (2015) The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Syst Appl 42:3016–3026 Wang J, Wei GW, Wei C, Wei Y (2020) MABAC method for multiple attribute group decision making under q-rung orthopair fuzzy environment. Def Technol 16:208–216 Pamucar D, Stevic Z, Zavadskas EK (2018) Integration of interval rough AHP and interval rough MABAC methods for evaluating university web pages. Appl Soft Comput 67:141–163 Peng XD, Yang Y (2016) Pythagorean fuzzy choquet integral based MABAC method for multiple attribute group decision making. Int J Intell Syst 31:989–1020 Xue YX, You JX, Lai XD, Liu HC (2016) An interval-valued intuitionistic fuzzy MABAC approach for material selection with incomplete weight information. Appl Soft Comput 38:703–713 Wei GW, Wei C, Wu J, Wang HJ (2019) Supplier selection of medical consumption products with a probabilistic linguistic MABAC method. Int J Environ Res Pub He 16:5082 Liang RX, He SS, Wang JQ, Chen K, Li L (2019) An extended MABAC method for multi-criteria group decision-making problems based on correlative inputs of intuitionistic fuzzy information. Comput Appl Math 38:112 Xu XG, Shi H, Zhang LJ, Liu HC (2019) Green supplier evaluation and selection with an extended MABAC method under the heterogeneous information environment. Sustainability 11:6616 Jia F, Liu YY, Wang XY (2019) An extended MABAC method for multi-criteria group decision making based on intuitionistic fuzzy rough numbers. Expert Syst Appl 127:241–255 Gong JW, Li Q, Yin LS, Liu HC (2020) Undergraduate teaching audit and evaluation using an extended MABAC method underq-rung orthopair fuzzy environment. Int J Intell Syst 35:1912–1933 Liu R, Hou LX, Liu HC, Lin WL (2020) Occupational health and safety risk assessment using an integrated SWARA-MABAC model under bipolar fuzzy environment. Comput Appl Math 39:276 Estiri M, Dahooie JH, Vanaki AS, Banaitisi A, Binkyte-Veliene A (2021) A multi attribute framework for the selection of high performance work systems the hybrid DEMATEL MABAC model. Econ Res 34(1):970–997 Liu PD, Pan Q, Xu HX (2021) Multi-attributive border approximation area comparison (MABAC) method based on normal q-rung orthopair fuzzy environment. J Intell Fuzzy Syst 40:9085–9111 Liu Y, Qin Y, Liu F, Rong Y (2021) GIBWM-MABAC approach for MAGDM under multi-granularity intuitionistic 2-tuple linguistic information model. J Amb Intel Hum Comput. https://doi.org/10.1007/s12652-021-03476-3 Zhao MW, Wei GW, Chen XD, Wei Y (2021) Intuitionistic fuzzy MABAC method based on cumulative prospect theory for multiple attribute group decision making. Int J Intell Syst 36:6337–6359 Liu F, Li TR, Wu J, Liu Y (2021) Modification of the BWM and MABAC method for MAGDM based on q-rung orthopair fuzzy rough numbers. Int J Mach Learn Cyber 12:2693–2715 Rong LL, Wang L, Liu PD, Zhu BY (2021) Evaluation of MOOCs based on multigranular unbalanced hesitant fuzzy linguistic MABAC method. Int J Intell Syst 36:5670–5713 Liu PD, Wang DY (2022) A 2-dimensional uncertain linguistic MABAC method for multiattribute group decision-making problems. Complex Intell Syst 8:349–360 Tang SQ, Wei GW, Chen XD (2022) Location selection of express distribution centre with probabilistic linguistic MABAC method based on the cumulative prospect theory. Informatica 33(1):131–150 Su Y, Zhao M, Wei GW, Wei C, Chen X (2022) An extended MABAC method based on prospect theory for multiple attribute group decision making under probabilistic uncertain linguistic environment. Iran J Fuzzy Syst 19(5):79–94 Tan JD, Liu Y, Senapati T, Garg H, Rong Y (2022) An extended MABAC method based on prospect theory with unknown weight information under Fermatean fuzzy environment for risk investment assessment in B&R. J Amb Intel Hum Comput. https://doi.org/10.1007/s12652-022-03769-1 Huang GQ, Xiao LM, Pedrycz W, Pamucar D, Zhang GB, Martinez L (2022) Design alternative assessment and selection: a novel Z-cloud rough number-based BWM-MABAC model. Inf Sci 603:149–189 Ahmad U, Khan A, Saeid AB (2023) Integrated multi-criteria group decision-making methods based on q-rung picture fuzzy sets for the identification of occupational hazards. Soft Comput. https://doi.org/10.1007/s00500-023-08154-4 Chen ZH, Luo W (2023) An integrated interval type-2 fuzzy rough technique for emergency decision making. Appl Soft Comput 137:110150 Wu SJ, Wei GW (2017) Picture uncertain linguistic aggregation operators and their application to multiple attribute decision making. Int J Knowl-Based In 21:243–256 Gül S (2020) Spherical fuzzy extension of DEMATEL (SF-DEMATEL). Int J Intell Syst 35:1329–1353 Wei GW (2008) Maximizing deviation method for multiple attribute decision making in intuitionistic fuzzy setting. Knowl Based Syst 21:833–836 Wu Y, Xu C, Zhang T (2018) Evaluation of renewable power sources using a fuzzy MCDM based on cumulative prospect theory: a case in China. Energy 147:1227–1239 Rani P, Mishra AR, Rezaei G, Liao HC, Mardani A (2020) Extended Pythagorean fuzzy TOPSIS method based on similarity measure for sustainable recycling partner selection. Int J Fuzzy Syst 22(2):735–747 Pamucar D, Stevic Z, Sremac S (2018) A new model for determining weight coefficients of criteria in MCDM models: full consistency method (FUCOM). Symmetry 10(9):393