Abstract
The hesitant and imprecise uncertainties widely exist in real decision-making problems. For solving the class of problems, this work is aimed at reconfiguring a novel method under the TOPSIS framework to solve the general uncertain decision problem that with both the ratings of alternatives and weights of criteria represented by interval-valued hesitant fuzzy (IVHF) information. Three novelties are proposed to support the reconfigured method. First, a parameterized approach for generating apt positive and negative IVHF reference solutions is proposed, which permits decision makers (DMs) to express their different aspiration strengths for fitting complex and uncertain decision scenarios and situations. Second, a novel distance for IVHF elements is constructed based on the modification of Wave-Hedges measurement to address the defects of the previous hesitant distances and to measure the separations of alternatives in TOPSIS. Third, a nine-step solution procedure of IVHF-TOSPSIS method is reconfigured to solve effectively the general problem that the ratings and weights are expressed with IVHF information. Finally, the reconfigured method is exploited to settle the carbon performance evaluation of industrial firms and some sensitivity and comparison analyses are conducted to validate the proposed method.





Similar content being viewed by others
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.References
Acuña-Soto C, Liern V, Pérez-Gladish B (2018) Normalization in TOPSIS-based approaches with data of different nature: application to the ranking of mathematical videos. Ann Oper Res. https://doi.org/10.1007/s10479-018-2945-5
Aktas A, Kabak M (2019) A hybrid hesitant fuzzy decision-making approach for evaluating solar power plant location sites. Arab J Sci Eng 44(8):7235–7247
Ameri AA, Pourghasemi HR, Cerda A (2018) Erodibility prioritization of sub-watersheds using morphometric parameters analysis and its mapping: a comparison among TOPSIS, VIKOR, SAW, and CF multi-criteria decision making models. Sci Total Environ 613:1385–1400
Boran FE, Genç S, Kurt M, Akay D (2009) A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Exp Syst Appl 36:11363–11368
Busch T, Weinhofer G, Hoffmann VH (2011) The carbon performance of the 100 largest US electricity producers. Util Policy 19:95–103
Celen A (2014) Comparative analysis of normalization procedures in TOPSIS method: with an application to Turkish deposit banking market. Informatica 25:185–208
Chamodrakas I, Leftheriotis I, Martakos D (2011) In-depth analysis and simulation study of an innovative fuzzy approach for ranking alternatives in multiple attribute decision making problems based on TOPSIS. Appl Soft Comput 11:900–907
Chen CT, Cheng HL (2009) A comprehensive model for selecting information system project under fuzzy environment. Int J Proj Manag 27:389–399
Chen SM, Lee LW (2010) Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method. Exp Syst Appl 37:2790–2798
Chen N, Xu ZS, Xia MM (2013) Interval-valued hesitant preference relations and their applications to group decision making. Knowl-Based Syst 37:528–540
Deza MM, Deza E (2009) Encyclopedia of Distances. Springer, Berlin
Dyckhoff H, Pedrycz W (1984) Generalized means as model of compensative connectives. Fuzzy Sets Syst 14:143–154
Farhadinia B (2014) Distance and similarity measures for higher order hesitant fuzzy sets. Knowl-Based Syst 55:43–48
Govindan K, Sivakumar R (2016) Green supplier selection and order allocation in a low-carbon paper industry: integrated multi-criteria heterogeneous decision-making and multi-objective linear programming approaches. Ann Oper Res 238:243–276
Hoffmann AO, Henry SF, Kalogeras N (2013) Aspirations as reference points: an experimental investigation of risk behavior over time. Theor Decis 75(2):193–210
Hsu CW, Kuo RJ, Chiou CY (2014) A multi-criteria decision-making approach for evaluating carbon performance of suppliers in the electronics industry. Int J Environ Sci Te 11:775–784
Hwang CL, Yoon KL (1981) Multiple attribute decision making: methods and applications: a state-of-the-art survey. Springer-Verlag, New York
Jasiewicz J, Netzel P, Stepinski T (2015) GeoPAT: a toolbox for pattern-based information retrieval from large geospatial databases. Comput Geosci 80:62–73
Joshi R (2019) A new multi-criteria decision making method based on intuitionistic fuzzy information and its application to fault detection in a machine. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-019-01322-1
Joshi D, Kumar S (2016) Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making. Eur J Oper Res 248:183–191
Joshi R, Kumar S (2017) Application of interval-valued intuitionistic fuzzy r-norm entropy in multiple attribute decision making. Int J Inform Manage Sci 28(3):233–251
Joshi R, Kumar S (2018) An intuitionistic fuzzy (δ, γ)-norm entropy with its application in supplier selection problems. Comput Appl Math 37(5):5624–5649
Joshi R, Kumar S (2019a) A novel fuzzy decision-making method using entropy weights-based correlation coefficients under intuitionistic fuzzy environment. Int J Fuzzy Syst 21(1):232–242
Joshi R, Kumar S (2019b) An intuitionistic fuzzy information measure of order-(α;β) with a new approach in supplier selection problems using an extended VIKOR method. J Appl Math Comput 60(1–2):27–50
Kuo RJ, Hsu CW, Chen YL (2015) Integration of fuzzy ANP and fuzzy TOPSIS for evaluating carbon performance of suppliers. Int J Environ Sci Te 12:3863–3876
Lahdelma R, Miettinen K, Salminen P (2005) Reference point approach for multiple decision makers. Eur J Oper Res 164:785–791
Laub J, Roth V, Buhmann JM, Müller KR (2006) On the information and representation of non-Euclidean pairwise data. Pattern Recogn 39:1815–1826
Li DQ, Zeng WY, Li JH (2015) New distance and similarity measures on hesitant fuzzy sets and their applications in multiple criteria decision making. Eng Appl Artif Intell 40:11–16
Liu W, Yang SH (2014) A novel method for multi-attribute group decision making with interval-valued intuitionistic uncertain linguistic information based on TOPSIS. In: 2014 International conference on management science and engineering 21th annual conference proceedings (pp. 193-199)
Mardani A, Jusoh A, Zavadskas EK (2015) Fuzzy multiple criteria decision-making techniques and applications–Two decades review from 1994 to 2014. Exp Syst Appl 42:4126–4148
Moorman T (2014) An empirical investigation of methods to reduce transaction costs. J Empir Financ 29:230–246
Onar SC, Oztaysi B, Kahraman C (2014) Strategic decision selection using hesitant fuzzy topsis and interval type-2 fuzzy AHP: a case study. Int J Comput Int Sys 7:1002–1021
Peng DH, Wang H (2014) Dynamic hesitant fuzzy aggregation operators in multi-period decision making. Kybernetes 43(5):715–736
Peng DH, Gao CY, Gao ZF (2013) Generalized hesitant fuzzy synergetic weighted distance measures and their application to multiple criteria decision-making. Appl Math Model 37:5837–5850
Peng DH, Wang TD, Gao CY (2014) Wang H (2014) Continuous hesitant fuzzy aggregation operators and their application to decision making under interval-valued hesitant fuzzy setting. Sci World J. https://doi.org/10.1155/2014/897304
Peng DH, Wang TD, Gao CY, Wang H (2017) Enhancing relative ratio method for MCDM via attitudinal distance measures of interval-valued hesitant fuzzy sets. Int J Mach Learn Cyb 8:1347–1368
Pérez-Fernández R, Alonso P, Bustince H, Díaz I, Montes S (2016) Applications of finite interval-valued hesitant fuzzy preference relations in group decision making. Inf Sci 326:89–101
Pinto A (2014) QRAM a qualitative occupational safety risk assessment model for the construction industry that incorporate uncertainties by the use of fuzzy sets. Safety Sci 63:57–76
Rodríguez RM, Martinez L, Torra V, Xu ZS, Herrera F (2014) Hesitant fuzzy sets: state of the art and future directions. Int J Intell Syst 29:495–524
Rodríguez RM, Bedregal B, Bustince H, Dong Y et al (2016) A position and perspective analysis of hesitant fuzzy sets on information fusion in decision making, Towards high quality progress. Inform Fusion 29:89–97
Safarzadeh S, Rasti-Barzoki M (2018) A modified lexicographic semi-order model using the best-worst method. J Decis Syst 27(2):78–91
Safarzadeh S, Khansefid S, Rasti-Barzoki M (2018) A group multi-criteria decision-making based on best-worst method. Comput Ind Eng 126:111–121
Seda AK, Hitzler P (2010) Generalized distance functions in the theory of computation. Comput J 53(4):443–464
Sun GD, Guan X, Yi X, Zhou Z (2018) An innovative TOPSIS approach based on hesitant fuzzy correlation coefficient and its applications. Appl Soft Comput 68:249–267
Torra V (2010) Hesitant fuzzy sets. Int J Intell Syst 25:529–539
Torra V, Narukawa Y (2009) On hesitant fuzzy sets and decision. In: The 18th IEEE international conference on fuzzy systems, Jeju Island, Korea, pp. 1378–1382
Torres-Sospedra J, Montoliu R, Trilles S, Belmonte Ó, Huerta J (2015) Comprehensive analysis of distance and similarity measures for Wi-Fi fingerprinting indoor positioning systems. Exp Syst Appl 42:9263–9278
Wang YJ (2014) A fuzzy multi-criteria decision-making model by associating technique for order preference by similarity to ideal solution with relative preference relation. Inf Sci 268:169–184
Wang YJ, Lee HS (2007) Generalizing TOPSIS for fuzzy multiple-criteria group decision-making. Comput Math Appl 53:1762–1772
Wang JQ, Wu JT, Wang J, Zhang HY, Chen XH (2016) Multi-criteria decision-making methods based on the Hausdorff distance of hesitant fuzzy linguistic numbers. Soft Comput 20:1621–1633
Xu ZS, Xia MM (2011) Distance and similarity measures for hesitant fuzzy sets. Inf Sci 181:2128–2138
Xu ZS, Zhang XL (2013) Hesitant fuzzy multi-attribute decision making based on TOPSIS with incomplete weight information. Knowl-Based Syst 52:53–64
Yager RR (1981) On a general class of fuzzy connectives. Fuzzy Sets Syst 4:235–242
Yang MS, Hussain Z (2019) Distance and similarity measures of hesitant fuzzy sets based on Hausdorff metric with applications to multi-criteria decision making and clustering. Soft Comput 23(14):5835–5848
Zavadskas EK, Turskis Z, Kildiene S (2014) State of art surveys of overviews on MCDM/MADM methods. Technol Econ Dev Econ 20:165–179
Zhang N, Wei GW (2013) Extension of VIKOR method for decision making problem based on hesitant fuzzy set. Appl Math Model 37:4938–4947
Zhang CQ, Wang C, Zhang ZM, Tian DZ (2019) A novel technique for multiple attribute group decision making in interval-valued hesitant fuzzy environments with incomplete weight information. J Ambient Intell Humaniz Comput 10(6):2429–2445
Zyoud SH, Fuchs-Hanusch D (2017) A bibliometric-based survey on AHP and TOPSIS techniques. Exp Syst Appl 78:158–181
Acknowledgements
The authors are very grateful to the Editor-in-Chief, professor Vincenzo Loia, and the anonymous referees for their insightful and constructive comments and suggestions which have helped to improve the paper. This work has been supported by the National Natural Science Funds of China (Nos. 71861018, 61364016 and 71272191), the Philosophy and Social Science Programs of Yunnan Province, China (No. YB2019067), the China Postdoctoral Science Foundation (Nos. 2015T80990 and 2014M550473), and the Applied Basic Research Programs of Yunnan Province, China (No. 2014FB136).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Peng, DH., Peng, B. & Wang, TD. Reconfiguring IVHF-TOPSIS decision making method with parameterized reference solutions and a novel distance for corporate carbon performance evaluation. J Ambient Intell Human Comput 11, 3811–3832 (2020). https://doi.org/10.1007/s12652-019-01603-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-019-01603-9