A dual probabilistic linguistic MARCOS approach based on generalized Dombi operator for decision-making

Saha, A.; Mishra, A. R.; Rani, P.; Senapati, T.; Yager, R. R.

doi:10.22111/ijfs.2023.7558

Document Type : Research Paper

Authors

¹ Department of Engineering Mathematics, College of Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram-522302, AP, India

² Department of Mathematics, Government College Raigaon, Satna, M P-485441, India

³ School of Mathematics and Statistics, Southwest University, Beibei-400715, Chongqing, China

⁴ Machine Intelligence Institute, Iona College, New Rochelle, NY 10801, USA

https://doi.org/10.22111/ijfs.2023.7558

Abstract

Dual probabilistic linguistic term sets (DPLTSs) are more powerful compare to probabilistic linguistic term sets, probabilistic hesitant fuzzy sets, hesitant fuzzy sets and intuitionistic fuzzy sets for the reason that they deal with both belongingness grades and non-belongingness grades along with their respective probabilities. On the other hand, the generalized Dombi operators have higher flexibility due to inclusion of two parameters. MARCOS (Measurements alternatives and ranking according to compromise solution) technique was developed by utilizing the utility degrees of options using the ideal and anti-ideal solutions. Here, we combine the merits of generalized Dombi operator and MARCOS and propose a DPL-MARCOS approach under dual probabilistic linguistic setting. In this methodology, the concepts of consistency and similarity between the experts are used to calculate their weights of subjective and objective types, respectively. For aggregating experts' preferences, we propose dual probabilistic linguistic- generalized Dombi weighted averaging aggregation operator. A biomass feedstock selection problem is furnished to show the applicability of our technique. We have considered coconut shell, coffee husk and sugarcane baggage as alternatives. The result shows that coffee husk is the most suitable option. The sensitivity assessment of parameter values reveals that our technique is stable. The comparative study proves that our model is more significant and realistic compare to the existing ones.

Keywords

References

[1] I. Badi, D. Pamucar, Supplier selection for steel-making company by using combined GREY-MARCOS methods,
Decision Making: Applications in Management and Engineering, 3 (2020), 37-47.

[2] N. Cagman, I. Deli, Products of FP-soft sets and their applications, Hacettepe Journal of Mathematics and Statistics,
41 (2012), 365-374.

[3] X. Cheng, J. Gu, Z. S. Xu, Venture capital group decision-making with interaction under probabilistic linguistic
environment, Knowledge-Based Systems, 140 (2018), 82-91.

[4] I. Deli, N. Cagman, Means of FP-soft sets and their applications, Hacettepe Journal of Mathematics and Statistics,
41 (2012), 615-625.

[5] J. L. Deng, Control problems on grey systems, Systems and Control Letters, 1 (1982), 288-294.

[6] A. Dey, T. Senapati, M. Pal, G. Chen, Pythagorean fuzzy soft RMS approach to decision making and medical
diagnosis, Afrika Matematika, 33(97) (2022). DOI:10.1007/s13370-022-01031-7.

[7] J. Dombi, The generalized Dombi operator family and the multiplicative utility function, In: V. E. Balas, J. Fodor,
A. R. V´arkonyi-K´oczy, (eds) Soft Computing Based Modeling in Intelligent Systems. Studies in Computational
Intelligence, vol 196. Springer, Berlin, Heidelberg. DOI:10.1007/978-3-642-00448-3-6.

[8] M. K. Ghorabaee, E. K. Zavadskas, M. Amiri, A. Esmaeili, Multi-criteria evaluation of green suppliers using an
extended WASPAS method with interval type-2 fuzzy sets, Journal of Cleaner Production, 137 (2016), 213-219.

[9] X. J. Gou, Z. S. Xu, H. C. Liao, Multi-criteria decision making based on Bonferroni means with hesitant fuzzy
linguistic information, Soft Computing, 21 (2017), 6515-6529.

[10] X. L. Han, S. R. Li, The priority method in view of consistency harmonious weight index, Systems EngineeringTheory Methodology, 3 (1994), 41-45.

[11] F. Herrera, L. Martinez. A 2-tuple fuzzy linguistic representation model for computing with words, IEEE Transactions on Fuzzy Systems, 8 (2000), 746-752.

[12] G. Isik, I. Kaya, A novel hesitant fuzzy linguistic term sets approach and its application on acceptance sampling
plans, Iranian Journal of Fuzzy Systems, 19(6) (2022), 175-192.

[13] C. Jana, T. Senapati, K. P. Shum, M. Pal, Bipolar fuzzy soft subalgebras and ideals of BCK/BCI-algebras based
on bipolar fuzzy points, Journal of Intelligent and Fuzzy Systems, 37(2) (2019), 2785-2795.

[14] A. Kobina, D. Liang, X. He, Probabilistic linguistic power aggregation operators for multi-criteria group decision
making, Symmetry, 9 (2017), 1-21.

[15] B. Li, Z. S. Xu, Y. X. Zhang, A probabilistic linguistic evaluation based multi-stage medical system selection process
related to referral system, Expert Systems with Applications, 170 (2020), 114523.

[16] H. Liao, X. Mi, Z. Xu, A survey of decision-making methods with probabilistic linguistic information?: Bibliometrics, preliminaries, methodologies, applications and future directions, Fuzzy Optimization and Decision Making, 19 (2010), 81-134.

[17] H. Liao, X. Wu, DNMA: A double normalization-based multiple aggregation method for multi-expert multi-criteria
decision making, Omega, 94 (2020), 102058. DOI:10.1016/j.omega.2019.04.001.

[18] P. Liu, F. Teng, Probabilistic linguistic TODIM method for selecting products through online product reviews,
Information Science, 485 (2019), 441-455.

[19] Q. Pang, H. Wang, Z. S. Xu, Probabilistic linguistic term sets in multi-attribute group decision making, Information
Science, 369 (2016), 128-143.

[20] S. Ramadass, R. Krishankumar, K. S. Ravichandran, H. Liao, S. Kar, Evaluation of cloud vendors from probabilistic
linguistic information with unknown/partial weight values, Applied Soft Computing, 97 (2020), 106801.

[21] R. M. Rodriguez, L. Martinez, F. Herrera, Hesitant fuzzy linguistic term sets for decision making, IEEE Transactions on Fuzzy Systems, 20 (2012), 109-119.

[22] Y. Rong, L. Yu, W. Niu, Y. Liu, T. Senapati, A. R. Mishra, MARCOS approach based upon cubic Fermatean fuzzy
set and its application in evaluation and selecting cold chain logistics distribution center, Engineering Applications
of Artificial Intelligence, 116 (2022), 105401. DOI:10.1016/j.engappai.2022.105401.

[23] A. Saha, T. Senapati, R. R. Yager, Hybridizations of generalized Dombi operators and Bonferroni mean operators under dual probabilistic linguistic environment for group decision-making, International Journal of Intelligent
Systems, 36(11) (2021), 6645-6679.

[24] A. Saha, V. Simic, T. Senapati, D. Dabic-Liletic, A. Ala, A dual hesitant fuzzy sets-based methodology for advantage
prioritization of zero-emission last-mile delivery solutions, IEEE Transactions on Fuzzy Systems, (2022). DOI:
10.1109/TFUZZ.2022.3164053.

[25] M. Stankovic, Z. Stevic, D. K. Das, M. Subotic, D. Pamucar, A new fuzzy MARCOS method for road traffic risk
analysis, Mathematics, 8 (2020), 1-18.

[26] Z. Stevic, N. Brkovic, A novel integrated FUCOM-MARCOS model for evaluation of human resources in a transport
company, Logistics, 4 (2020), 1-14.

[27] Z. Stevic, D. Pamucar, A. Puska, P. Chatterjee, Sustainable supplier selection in healthcare industries using a new
MCDM method: Measurement alternatives and ranking according to compromise solution (MARCOS), Computers
and Industrial Engineering, 140 (2020), 106231.

[28] A. Ulutas, D. Karabasevic, G. Popovic, D. Stanujkic, P. T. Nguyen, C. Karakoy, Development of a novel integrated
CCSD-ITARA-MARCOS decision-making approach for stackers selection in a logistics system, Mathematics, 8 (2020), 1-15.

[29] W. Xie, Z. S. Xu, Z. Ren, Dual probabilistic linguistic term set and its application on the multi-criteria group
decision-making problems, in: 2017, IEEE International Conference on Industrial Engineering and Engineering
Management, (2017), 1469-1474.

[30] W. Xie, Z. S. Xu, Z. Ren, E. H. Viedma, A new multi-criteria decision-making model based on incomplete dual
probabilistic linguistic preference relations, Applied Soft Computing, 91 (2020), 106237.

[31] G. L. Xu, S. P. Wan, J. Y. Dong, An entropy-based method for probabilistic linguistic group decision making and
its application of selecting car sharing platforms, Informatica, 31(3) (2020), 621-658.

[32] L. A. Zadeh, The concept of a linguistic variable and its application to approximate reasoning-I, Information
Science, 8 (1975), 199-249.

[33] X. Zhang, X. Xing, Probabilistic linguistic VIKOR method to evaluate green supply chain initiatives, Sustainability, 9 (2017), 1-18.

A dual probabilistic linguistic MARCOS approach based on generalized Dombi operator for decision-making

References

References

Volume 20, Issue 2March and April 2023Pages 83-102

Volume 20, Issue 2
March and April 2023
Pages 83-102