Abstract
The fundamental principle of QUALIFLEX is to treat the cardinal and ordinal information in a correct way and to take all the possible rankings of alternatives into account. The focus of QUALIFLEX is the pairwise comparison of alternatives with respect to each attribute under all possible permutations. The optimal permutation is recognized through the comprehensive concordance/discordance index, and the best alternative will be identified according to it.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Paelinck JHP (1976) Qualitative multiple criteria analysis, environmental protection and multiregional development. Papers Region Scie Assoc 36(1):59–74
Paelinck JHP (1978) QUALIFLEX: a flexible multiple-criteria method. Econ Lett 1(3):193–197
Alinezhad A, Esfandiari N (2012) Sensitivity analysis in the QUALIFLEX and VIKOR methods. J Optim Industr Eng
Chen TY, Tsui CW (2012) Intuitionistic fuzzy QUALIFLEX method for optimistic and pessimistic decision making. Adv Inform Sci Serv Sci 4(14):219–226
Chen TY (2014) Interval-valued intuitionistic fuzzy QUALIFLEX method with a likelihood-based comparison approach for multiple criteria decision analysis. Inf Sci 261:149–169
Chen TY (2013) Data construction process and qualiflex-based method for multiple-criteria group decision making with interval-valued intuitionistic fuzzy sets. Int J Inf Technol Decis Mak 12(3):425–467
Zhang XL (2016) Multicriteria Pythagorean fuzzy decision analysis: a hierarchical QUALIFLEX approach with the closeness index-based ranking methods. Inf Sci 330:104–124
Zhang XL, Xu ZS (2015) Hesitant fuzzy QUALIFLEX approach with a signed distance-based comparison method for multiple criteria decision analysis. Expert Syst Appl 42(2):873–884
Zhang Z (2017) Multi-criteria decision-making using interval-valued hesitant fuzzy QUALIFLEX methods based on a likelihood-based comparison approach. Neural Comput Appl 28(7):1835–1854
Li J, Wang JQ (2017) An Extended QUALIFLEX method under probability hesitant fuzzy environment for selecting green suppliers. Int J Fuzzy Syst 19(6):1866–1879
Peng HG, Zhang HY, Wang JQ (2018) Probability multi-valued neutrosophic sets and its application in multi-criteria group decision-making problems. Neural Comput Appl 30(2):563–583
Dincer H, Yuksel S (2019) IT2-Based fuzzy hybrid decision making approach to soft computing. IEEE Access 7:15932–15944
Dincer H, Yuksel S, Korsakien R, Raisiene AG, Bilan Y (2019) IT2 hybrid decision-making approach to performance measurement of internationalized firms in the baltic states. Sustainability 11(1):296
Chen TY, Chang CH, Lu JFR (2013) The extended QUALIFLEX method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making. Europ J Oper Res 226(3):615–625
Wang JC, Tsao CY, Chen TY (2015) A likelihood-based QUALIFLEX method with interval type-2 fuzzy sets for multiple criteria decision analysis. Soft Comput 19(8):2225–2243
Zhang XL, Xu ZS, Liu MF (2016) Hesitant trapezoidal fuzzy QUALIFLEX method and its application in the evaluation of green supply chain initiatives. Sustainability 8(9)
Tian C, Zhang WY, Zhang S, Peng JJ (2019) An extended single-valued neutrosophic projection-based qualitative flexible multi-criteria decision-making method. Mathematics 7(1):16
Xue YX, You JX, Zhao X, Liu HC (2016) An integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information. Int J Product Res 54(18):5452–5467
Tian ZP, Wang J, Wang JQ, Zhang HY (2016) A likelihood-based qualitative flexible approach with hesitant fuzzy linguistic information. Cognitive Comput 8(4):670–683
Dong JY, Chen Y, Wan SP (2018) A cosine similarity based QUALIFLEX approach with hesitant fuzzy linguistic term sets for financial performance evaluation. Appl Soft Comput 69:316–329
Tian ZP, Wang J, Wang JQ, Zhang HY (2017) Simplified neutrosophic linguistic multi-criteria group decision-making approach to green product development. Group Decision Negoti 26(3):597–627
Tian XL, Xu ZS, Wang XX, Gu J, Alsaadi FE (2019) Decision models to find a promising start-up firm with QUALIFLEX under probabilistic linguistic circumstance. Int J Inform Technol Decision Making 18(4):1379–1402
Feng XQ, Liu Q, Wei CP (2019) Probabilistic linguistic QUALIFLEX approach with possibility degree comparison. J Intell Fuzzy Syst 36(1):719–730
Widyanto HA, Dalimunthe Z (2015) Evaluation criteria of venture capital firms investing on indonesians’ SME. Soc Sci Electron Publishing
Tversky A, Kahneman D (1992) Advances in prospect-theory-Cumulative representation of uncertainty. J Risk Uncertainty 5(4):297–323
Abdellaoui M (2000) Parameter-free elicitation of utility and probability weighting functions. Manage Sci 46(11):1497–1512
Zeng JM (2007) An experimental test on cumulative prospect theory. J Jinan Univ 28(1):44–472
Tian XL, Xu ZS, Jing G, Herrera-Viedma E (2018) How to select a promising enterprise for venture capitalists with prospect theory under intuitionistic fuzzy circumstance? Appl Soft Comput 67:756–763
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Tian, X., Xu, Z. (2021). QUALIFLEX Based on PT with Probabilistic Linguistic Information. In: Fuzzy Decision-Making Methods Based on Prospect Theory and Its Application in Venture Capital. Uncertainty and Operations Research. Springer, Singapore. https://doi.org/10.1007/978-981-16-0243-6_3
Download citation
DOI: https://doi.org/10.1007/978-981-16-0243-6_3
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-0242-9
Online ISBN: 978-981-16-0243-6
eBook Packages: Business and ManagementBusiness and Management (R0)