Abstract
The flue gas desulfurization (FGD) process eliminates Sulphur dioxides from flue gas produced by the combustion of fossil fuels in furnaces, boilers, and other sources. Limestone is an essential element for the FGD process in coal-fired thermal power plants. FGD system contributes efficaciously to the prevention of air pollution through its limestone/gypsum treatment in greater reliability, higher efficiency, and more capability. The selection of the limestone suppliers is thus a crucial task to improve environmental aspects and reduce cost. To optimize the selection of limestone suppliers, appropriate criteria determination and an effective solution approach are the central undertakings, which need to be made scientifically. Addressing the multi-criteria nature of the selection process, this study introduces a new Multi-Criteria-Decision-Making (MCDM) approach to evaluate supplier selection and deliver a group decision making (GDM) method in an ambiguous and fuzzy environment. The proposed method also takes decision makers’ judgments into account in times of pressure, bias, and lack of expertise during the evaluation process. Consequently, this study, for the first time, integrates the Pythagorean Fuzzy Sets (PFSs), Simple Additive Weighting (SAW), and Evaluation Based on Distance from Average Solution (EDAS) under GDM setting. This paper, also for the first time, includes the analyses of an evaluation for the right supplier selection in a thermal power plant. A real case study from Turkey is applied to illustrate the validity of the proposed approach. Sensitivity analysis and comparison of the results with the existing techniques are also presented to verify the significance of the found outcome.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
Enquiries about data availability should be directed to the authors.
References
Abdullah L, Goh P (2019) Decision making method based on Pythagorean fuzzy sets and its application to solid waste management. Complex Intell Syst 5:185–198. https://doi.org/10.1007/s40747-019-0100-9
Ak MF, Gul M (2019) AHP–TOPSIS integration extended with Pythagorean fuzzy sets for information security risk analysis. Complex Intell Syst 5:113–126. https://doi.org/10.1007/s40747-018-0087-7
Alipour M, Hafezi R, Rani P et al (2021) A new Pythagorean fuzzy-based decision-making method through entropy measure for fuel cell and hydrogen components supplier selection. Energy 234:121208. https://doi.org/10.1016/j.energy.2021.121208
Atanassov KT (1999) Intuitionistic fuzzy sets: theory and applications. Physica-Verlag HD, Heidelberg
Ayyildiz E, Erdogan M, Taskin Gumus A (2021) A Pythagorean fuzzy number-based integration of AHP and WASPAS methods for refugee camp location selection problem: a real case study for Istanbul, Turkey. Neural Comput Appl 33:15751–15768. https://doi.org/10.1007/s00521-021-06195-0
Bakioglu G, Atahan AO (2021) AHP integrated TOPSIS and VIKOR methods with Pythagorean fuzzy sets to prioritize risks in self-driving vehicles. Appl Soft Comput 99:106948. https://doi.org/10.1016/j.asoc.2020.106948
Biswas A, Sarkar B (2019) Pythagorean fuzzy TOPSIS for multicriteria group decision-making with unknown weight information through entropy measure. Int J Intell Syst 34:1108–1128. https://doi.org/10.1002/int.22088
Bolturk E (2018) Pythagorean fuzzy CODAS and its application to supplier selection in a manufacturing firm. J Enterp Inf Manag 31:550–564. https://doi.org/10.1108/JEIM-01-2018-0020
Brauers WKM, Zavadskas EK (2006) The MOORA method and its application to privatization in a transition economy. Control Cybern 35:445–469
Büyüközkan G, Çifçi G (2012) A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert Syst Appl 39:3000–3011. https://doi.org/10.1016/j.eswa.2011.08.162
Buyukozkan G, Gocer F (2021) A Novel Approach Integrating AHP and COPRAS Under Pythagorean Fuzzy Sets for Digital Supply Chain Partner Selection. IEEE Trans Eng Manag 68:1486–1503. https://doi.org/10.1109/TEM.2019.2907673
Buyukozkan G, Göçer F (2019) Prioritizing the strategies to enhance smart city logistics by ıntuitionistic fuzzy CODAS. In: Proceedings of the 2019 Conference of the ınternational fuzzy systems association and the european society for fuzzy logic and technology (EUSFLAT 2019). Atlantis Press, Paris, France, pp 805–811
Büyüközkan G, Göçer F (2021) Evaluation of software development projects based on integrated Pythagorean fuzzy methodology. Expert Syst Appl 183:115355. https://doi.org/10.1016/j.eswa.2021.115355
Büyüközkan G, Göçer F (2017) Application of a new combined intuitionistic fuzzy MCDM approach based on axiomatic design methodology for the supplier selection problem. Appl Soft Comput 52:1222–1238. https://doi.org/10.1016/j.asoc.2016.08.051
Büyüközkan G, Göçer F (2018) An extension of ARAS methodology under Interval Valued Intuitionistic Fuzzy environment for Digital Supply Chain. Appl Soft Comput 69:634–654. https://doi.org/10.1016/j.asoc.2018.04.040
Büyüközkan G, Göçer F (2019) Smart medical device selection based on intuitionistic fuzzy Choquet integral. Soft Comput 23:10085–10103. https://doi.org/10.1007/s00500-018-3563-5
Büyüközkan G, Göçer F, Feyzioğlu O (2018) Cloud computing technology selection based on interval-valued intuitionistic fuzzy MCDM methods. Soft Comput 22:5091–5114. https://doi.org/10.1007/s00500-018-3317-4
Büyüközkan G, Göçer F, Karabulut Y (2019) A new group decision making approach with IF AHP and IF VIKOR for selecting hazardous waste carriers. Measurement 134:66–82. https://doi.org/10.1016/j.measurement.2018.10.041
Büyüközkan G, Göçer F, Uztürk D (2021) a novel pythagorean fuzzy set integrated choquet integral approach for vertical farming technology assessment. Comput Ind Eng. https://doi.org/10.1016/j.cie.2021.107384
Büyüközkan G, Güler M (2020) Smart watch evaluation with integrated hesitant fuzzy linguistic SAW-ARAS technique. Measurement 153:107353. https://doi.org/10.1016/j.measurement.2019.107353
Chai J, Liu JNK, Ngai EWT (2013) Application of decision-making techniques in supplier selection: a systematic review of literature. Expert Syst Appl 40:3872–3885. https://doi.org/10.1016/j.eswa.2012.12.040
Chen T-Y (2012) Comparative analysis of SAW and TOPSIS based on interval-valued fuzzy sets: discussions on score functions and weight constraints. Expert Syst Appl 39:1848–1861. https://doi.org/10.1016/j.eswa.2011.08.065
Chen T-Y (2019) A novel PROMETHEE-based method using a Pythagorean fuzzy combinative distance-based precedence approach to multiple criteria decision making. Appl Soft Comput 82:105560. https://doi.org/10.1016/j.asoc.2019.105560
Chen T-Y (2018) Remoteness index-based Pythagorean fuzzy VIKOR methods with a generalized distance measure for multiple criteria decision analysis. Inf Fusion 41:129–150. https://doi.org/10.1016/j.inffus.2017.09.003
Chou S-Y, Chang Y-H, Shen C-Y (2008) A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes. Eur J Oper Res 189:132–145. https://doi.org/10.1016/j.ejor.2007.05.006
Churchman CW, Ackoff RL (1954) An approximate measure of value. J Oper Res Soc Am 2:172–187. https://doi.org/10.1287/opre.2.2.172
Çoban V, Onar SÇ (2018) Pythagorean fuzzy engineering economic analysis of solar power plants. Soft Comput 22:5007–5020. https://doi.org/10.1007/s00500-018-3234-6
Deb R, Roy S (2021) A software defined network information security risk assessment based on Pythagorean fuzzy sets. Expert Syst Appl 183:115383. https://doi.org/10.1016/j.eswa.2021.115383
Fishburn PC (1967) Letter to the editor—additive utilities with incomplete product sets: application to priorities and assignments. Oper Res 15:537–542. https://doi.org/10.1287/opre.15.3.537
Garg H (2019) Special issue on “Pythagorean fuzzy set and its extensions in decision-making process.” Complex Intell Syst 5:91–92. https://doi.org/10.1007/s40747-019-0112-5
Ghorabaee MK, Zavadskas EK, Turskis ZZ, Antucheviciene J (2016) A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. Econ Comput Econ Cybern Stud Res 50:25–44
Gocer F (2021) A novel interval value extension of picture fuzzy sets into group decision making: an approach to support supply chain sustainability in catastrophic disruptions. IEEE Access 9:117080–117096. https://doi.org/10.1109/ACCESS.2021.3105734
Göçer F (2021) Improving sustainable supplier evaluation by an integrated MCDM method under pythagorean fuzzy environment. Cumhur Sci J 42:218–235. https://doi.org/10.17776/csj.735674
Gocer F, Sener N (2021) Spherical fuzzy extension of AHP-ARAS methods integrated with modified k-means clustering for logistics hub location problem. Expert Syst Early View 39(2):e12886. https://doi.org/10.1111/exsy.12886
Hwang C-L, Yoon K (1981a) Multiple attribute decision making methods and applications a state-of-the-art survey. Springer, Berlin
Hwang CL, Yoon K (1981b) Multiple attribute decision making-methods and application. Springer, New York
Jiang G-J, Chen H-X, Sun H-H et al (2021) An improved multi-criteria emergency decision-making method in environmental disasters. Soft Comput 25:10351–10379. https://doi.org/10.1007/s00500-021-05826-x
Kabak Ö, Ervural B (2017) Multiple attribute group decision making: a generic conceptual framework and a classification scheme. Knowl-Based Syst 123:13–30. https://doi.org/10.1016/j.knosys.2017.02.011
Kahraman C, Oztaysi B, Otay I, Onar SC (2021) Extensions of ordinary fuzzy sets: a comparative literature review. In: Intelligent and fuzzy techniques: smart and ınnovative solutions. pp 1655–1665
Kaliszewski I, Podkopaev D (2016) Simple additive weighting—a metamodel for multiple criteria decision analysis methods. Expert Syst Appl 54:155–161. https://doi.org/10.1016/j.eswa.2016.01.042
Keshavarz Ghorabaee M, Zavadskas EK, Amiri M, Turskis Z (2016) Extended EDAS method for fuzzy multi-criteria decision-making: an application to supplier selection. Int J Comput Commun Control 11:358–371
Keshavarz Ghorabaee M, Zavadskas EK, Olfat L, Turskis Z (2015) Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica 26:435–451. https://doi.org/10.15388/Informatica.2015.57
Li H, Su L, Cao Y, Lv L (2019) A pythagorean fuzzy TOPSIS method based on similarity measure and its application to project delivery system selection. J Intell Fuzzy Syst 37:7059–7071. https://doi.org/10.3233/JIFS-181690
Li P, Liu J, Wei C, Liu J (2021) A new EDAS method based on prospect theory for Pythagorean fuzzy set and its application in selecting investment projects for highway. Kybernetes Early Acce: https://doi.org/10.1108/K-01-2021-0066
Liang D, Xu Z (2017) The new extension of TOPSIS method for multiple criteria decision making with hesitant Pythagorean fuzzy sets. Appl Soft Comput 60:167–179. https://doi.org/10.1016/j.asoc.2017.06.034
Liang D, Zhang Y, Xu Z, Jamaldeen A (2019) Pythagorean fuzzy VIKOR approaches based on TODIM for evaluating internet banking website quality of Ghanaian banking industry. Appl Soft Comput 78:583–594. https://doi.org/10.1016/j.asoc.2019.03.006
Liu C, Rani P, Pachori K (2021) Sustainable circular supplier selection and evaluation in the manufacturing sector using Pythagorean fuzzy EDAS approach. J Enterp Inf Manag Early Acce: https://doi.org/10.1108/JEIM-04-2021-0187
Liu S, Chan FTS, Ran W (2016) Decision making for the selection of cloud vendor: an improved approach under group decision-making with integrated weights and objective/subjective attributes. Expert Syst Appl 55:37–47. https://doi.org/10.1016/j.eswa.2016.01.059
MacCrimmon KR (1968) Decisionmaking among multiple-attribute alternatives: a survey and consolidated approach., RM-4823-AR. RAND Corporation, Santa Monica, Calif
Melani AHA, Murad CA, Caminada Netto A et al (2018) Criticality-based maintenance of a coal-fired power plant. Energy 147:767–781. https://doi.org/10.1016/j.energy.2018.01.048
Mishra AR, Mardani A, Rani P, Zavadskas EK (2020) A novel EDAS approach on intuitionistic fuzzy set for assessment of health-care waste disposal technology using new parametric divergence measures. J Clean Prod 272:122807. https://doi.org/10.1016/j.jclepro.2020.122807
Molla MU, Giri BC, Biswas P (2021) Extended PROMETHEE method with Pythagorean fuzzy sets for medical diagnosis problems. Soft Comput 25:4503–4512. https://doi.org/10.1007/s00500-020-05458-7
Muralikrishna IV., Manickam V (2017) Air Pollution Control Technologies. In: Environmental Management. Elsevier, pp 337–397
Nobre FF, Trotta LTF, Gomes LFAM (1999) Multi-criteria decision making—an approach to setting priorities in health care. Stat Med 18:3345–3354. https://doi.org/10.1002/(SICI)1097-0258(19991215)18:23%3c3345::AID-SIM321%3e3.0.CO;2-7
Opricovic S (1998) Multicriteria optimization of civil engineering systems. Fac Civ Eng Belgrade 2:5–21
Ozdemir Y, Gul M (2019) Measuring development levels of NUTS-2 regions in Turkey based on capabilities approach and multi-criteria decision-making. Comput Ind Eng 128:150–169. https://doi.org/10.1016/j.cie.2018.12.035
Peng X, Selvachandran G (2017) Pythagorean fuzzy set: state of the art and future directions. Artif Intell Rev 52:1873–1927. https://doi.org/10.1007/s10462-017-9596-9
Peng X, Yang Y (2015) Some results for pythagorean fuzzy sets. Int J Intell Syst 30:1133–1160. https://doi.org/10.1002/int.21738
Peng X, Zhang X, Luo Z (2020) Pythagorean fuzzy MCDM method based on CoCoSo and CRITIC with score function for 5G industry evaluation. Artif Intell Rev 53:3813–3847. https://doi.org/10.1007/s10462-019-09780-x
Pérez-Domínguez L, Rodríguez-Picón LA, Alvarado-Iniesta A et al (2018) MOORA under pythagorean fuzzy set for multiple criteria decision making. Complexity 2018:1–10. https://doi.org/10.1155/2018/2602376
Rani P, Mishra AR, Mardani A et al (2020) Pythagorean Fuzzy SWARA–VIKOR framework for performance evaluation of solar panel selection. Sustainability 12:4278. https://doi.org/10.3390/su12104278
Rani P, Mishra AR, Pardasani KR et al (2019) A novel VIKOR approach based on entropy and divergence measures of Pythagorean fuzzy sets to evaluate renewable energy technologies in India. J Clean Prod 238:117936. https://doi.org/10.1016/j.jclepro.2019.117936
Ren P, Xu Z, Gou X (2016) Pythagorean fuzzy TODIM approach to multi-criteria decision making. Appl Soft Comput 42:246–259. https://doi.org/10.1016/j.asoc.2015.12.020
Saaty TL (1980) The analytic hierarchy process: planning, priority setting, resource allocation. McGraw, New York
Sarkar B, Biswas A (2021) Pythagorean fuzzy AHP-TOPSIS integrated approach for transportation management through a new distance measure. Soft Comput 25:4073–4089. https://doi.org/10.1007/s00500-020-05433-2
Wang Y, Li J (2019) Spatial spillover effect of non-fossil fuel power generation on carbon dioxide emissions across China’s provinces. Renew Energy 136:317–330. https://doi.org/10.1016/j.renene.2019.01.012
Xie Y, Zhou Y, Peng Y et al (2021) An extended pythagorean fuzzy approach to group decision-making with incomplete preferences for analyzing balanced scorecard-based renewable energy investments. IEEE Access 9:43020–43035. https://doi.org/10.1109/ACCESS.2021.3065294
Yager RR (2013) Pythagorean fuzzy subsets. In: 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS). IEEE, pp 57–61
Yager RR (2014) Pythagorean membership grades in multicriteria decision making. IEEE Trans Fuzzy Syst 22:958–965. https://doi.org/10.1109/TFUZZ.2013.2278989
Yager RR, Abbasov AM (2013) Pythagorean membership grades, complex numbers, and decision making. Int J Intell Syst 28:436–452. https://doi.org/10.1002/int.21584
Yanmaz O, Turgut Y, Can EN, Kahraman C (2020) Interval-valued Pythagorean Fuzzy EDAS method: an application to car selection problem. J Intell Fuzzy Syst 38:4061–4077. https://doi.org/10.3233/JIFS-182667
Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
Zeng S, Chen J, Li X (2016) A hybrid method for pythagorean fuzzy multiple-criteria decision making. Int J Inf Technol Decis Mak 15:403–422. https://doi.org/10.1142/S0219622016500012
Zhang X, Xu Z (2014) Extension of TOPSIS to multiple criteria decision making with pythagorean fuzzy sets. Int J Intell Syst 29:1061–1078. https://doi.org/10.1002/int.21676
Zhou F, Chen T-Y (2021) An extended Pythagorean fuzzy VIKOR method with risk preference and a novel generalized distance measure for multicriteria decision-making problems. Neural Comput Appl 33:11821–11844. https://doi.org/10.1007/s00521-021-05829-7
Acknowledgements
Author kindly expresses his appreciation for the support of industry experts.
Funding
The authors have not disclosed any funding.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
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
Göçer, F. Limestone supplier selection for coal thermal power plant by applying integrated PF-SAW and PF-EDAS approach. Soft Comput 26, 6393–6414 (2022). https://doi.org/10.1007/s00500-022-07157-x
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00500-022-07157-x