Abstract
This chapter develops a new version of the multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) in the Pythagorean fuzzy environment. MULTIMOORA is one of the most robust multi-criteria decision-making (MCDM) techniques since it combines the additive, multiplicative, and reference point utility functions. There are two main approaches when implementing MULTIMOORA. Either using the dominance theory or by aggregating the values of three utility functions. In the latter approach, the results of the additive and multiplicative functions are defuzzified, while the result of the reference point function is already a crisp value since it relies on the distance from the ideal situation. In fact, a distance between two fuzzy values cannot be definitely determined. Hence, it is more convenient to define distance using fuzzy sets rather than a crisp value. Consequently, this study will adopt the aggregation approach in which distances are defined by Pythagorean fuzzy sets. As a result, defuzzification is employed only in the final step for ranking. At this point, the accuracy function can be also employed with the score function to make the comparison more discriminatory. In addition, newly proposed aggregation operators are exploited. These operators guarantee fair treatment among the evaluation criteria since most of the aggregation operators have a flaw that might result in a biased treatment and false ranking in certain situations. A practical example that considers the evaluation of energy storage technologies is provided to illustrate the developed technique and to make a comparative analysis.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Asante D, He Z, Adjei NO, Asante B (2020) Exploring the barriers to renewable energy adoption utilising MULTIMOORA—EDAS method. Energy Policy 142:111479. https://doi.org/10.1016/j.enpol.2020.111479
Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87–96
Atanassov KT (1999) Intuitionistic Fuzzy sets: theory and applications. Springer Pyhsica-Verlag Heidelberg, New York, NY
Brauers WKM, Zavadskas EK (2006) The MOORA method and its application to privatization in a transition economy. Control Cybern 35(2):445–496
Brauers WKM, Zavadskas EK (2010) Project management by MULTIMOORA as an instrument for transition economies. Technol Econ Dev Econ Baltic J Sustain 16(1):5–24
Brauers WKM, Zavadskas EK (2012) Robustness of MULTIMOORA: a method for multi-objective optimization. Informatica 23(1):1–25
Chen S, Wang J, Wang T (2019) Cloud-based ERP system selection based on extended probabilistic linguistic MULTIMOORA method and Choquet integral operator. Comp Appl Math 38. https://doi.org/10.1007/s40314-019-0839-z.
Chen Y, Ran Y, Wang Z, Li X, Yang X, Zhang G (2020) An extended MULTIMOORA method based on OWGA operator and Choquet integral for risk prioritization identification of failure modes. Eng Appl Artif Intell 91:103605. https://doi.org/10.1016/j.engappai.2020.103605
Çolak M, Kaya I (2020) Multi-criteria evaluation of energy storage technologies based on hesitant fuzzy information: a case study for Turkey. J Energy Storage 28:101211. https://doi.org/10.1016/j.est.2020.101211
Crampes C, Trochet J-M (2019) Economics of stationary electricity storage with various charge and discharge durations. J Energy Storage J Energy Storage 24:100746. https://doi.org/10.1016/j.est.2019.04.020
Dahooie JH, Zavadskas EK, Firoozfar HR, Vanaki AS, Mohammadi N, Brauers WKM (2019) An improved fuzzy MULTIMOORA approach for multi-criteria decision making based on objective weighting method (CCSD) and its application to technological forecasting method selection. Eng Appl Artif Intell 79:114–128
Dai W, Zhong Q, Qi C (2020) Multi-stage multi-attribute decision-making method based on the prospect theory and triangular fuzzy MULTIMOORA. Soft Comput 24:9429–9440
Dehghani-Sanij AR, Tharumalingama E, Dusseault MB, Fraser R (2019) Study of energy storage systems and environmental challenges of batteries. Renew Sustain Energy Rev 104:192–208
Dizdar EN, Ünver M (2019) The assessment of occupational safety and health in Turkey by applying a decision-making method; MULTIMOORA. Hum Ecol Risk Assess. https://doi.org/10.1080/10807039.2019.1600399
Edington ANC (2019) The role of long duration energy storage in decarbonizing power systems. A thesis Submitted to the Institute for Data, Systems, and Society in partial fulfillment of the requirements for the degree of Master of Science in Technology and Policy at the Massachusetts Institute of Technology.
Ejegwa PA (2020) Distance and similarity measures for Pythagorean fuzzy sets. Granular Comput 5:225–238. https://doi.org/10.1007/s41066-018-00149-z
Fedajev A, Stanujkic D, Karabašević D, Brauers WKM, Zavadskas EK (2020) Assessment of progress towards “Europe 2020” strategy targets by using the MULTIMOORA method and the Shannon Entropy Index. J Clean Prod 244:118895. https://doi.org/10.1016/j.jclepro.2019.118895
Garg H (2016) A novel accuracy function under interval-valued Pythagorean fuzzy environment for solving multi-criteria decision making problem J. Intel Fuzzy Syst. 31(1):529–540
Garg H (2016) A new generalized Pythagorean fuzzy information aggregation using Einstein operations and its application to decision making. Int J Intel Syst. 31(9):886–920
Garg H (2018) Generalized Pythagorean fuzzy geometric interactive aggregation operators using Einstein operations and their application to decision making. J Experi Theor Artif Intel 30(6):763–794
Garg H (2018) New exponential operational laws and their aggregation operators for interval-valued Pythagorean fuzzy multicriteria decision-making. Int J Intel Syst. 33(3):653–683
Garg H (2019) New logarithmic operational laws and their aggregation operators for Pythagorean fuzzy set and their applications. Int J Intell Syst 34(1):82–106
Garg H (2019) Novel neutrality operation–based Pythagorean fuzzy geometric aggregation operators for multiple attribute group decision analysis. J Intell Syst 34(10):2459–2489
Garg H (2020) Neutrality operations-based Pythagorean fuzzy aggregation operators and its applications to multiple attribute group decision-making process. J Amb Intell Human Comput 11:3021–3041
Gündoğdu FK (2020) A spherical fuzzy extension of MULTIMOORA method. J Intell Fuzzy Syst 38(1):963–978
Gündoğdu FK, Kahraman C (2019) Spherical fuzzy sets and spherical fuzzy TOPSIS method. J Intell Fuzzy Syst 36(1):337–352
Guney MS, Tepe Y (2017) Classification and assessment of energy storage systems. Renew Sustain Energy Rev 75:1187–1197
Hafezalkotob A, Hafezalkotob A, Liao H, Herrera F (2019) An overview of MULTIMOORA for multi-criteria decision-making: theory, developments, applications, and challenges. Inform Fusion 51:145–177
Hussian Z, Yang M-S (2019) Distance and similarity measures of Pythagorean fuzzy sets based on the Hausdorff metric with application to fuzzy TOPSIS. Int J Intell Syst. 34(10):2633–2654
Khan N, Dilshad S, Khalid R, Kalair AR, Abas N (2019) Review of energy storage and transportation of energy. Energy Storage. https://doi.org/10.1002/est2.49
Krishan O, Suhag S (2018) An updated review of energy storage systems: classification and applications in distributed generation power systems incorporating renewable energy resources. Energy Res 43(12):6171–6210
Lee J, Srimuka P, Fleischmann S, Su X, Hatton TA, Presser V (2019) Redox-electrolytes for non-flow electrochemical energy storage: a critical review and best practice. Prog Mater Sci 101:46–89
Li X-H, Huang L, Li Q, Chen Liu H-C (2020) Passenger satisfaction evaluation of public transportation using Pythagorean fuzzy MULTIMOORA method under large group environment. Sustainability 12:4996. https://doi.org/10.3390/su12124996
Liang D, Darko AP, Xu Z, Wang M (2019) Aggregation of dual hesitant fuzzy heterogeneous related information with extended Bonferroni mean and its application to MULTIMOORA. Comput Ind Eng 135:156–176
Liang D, Darko AP, Zeng J (2019) Interval-valued Pythagorean fuzzy power average-based MULTIMOORA method for multi-criteria decision-making. J Exp Theor Artif Intell. https://doi.org/10.1080/0952813X.2019.1694589
Liang W, Zhao G, Hong C (2019) Selecting the optimal mining method with extended multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) approach. Neural Comput Appl 31:5871–5886
Liao H, Qin R, Gao C, Wu X, Hafezalkotob A, Herrera F (2019) Score-HeDLiSF: a score function of hesitant fuzzy linguistic term set based on hesitant degrees and linguistic scale functions: An application to unbalanced hesitant fuzzy linguistic MULTIMOORA. Inform Fusion 48:39–54
Lin M, Huang C, Xu Z (2020) MULTIMOORA based MCDM model for site selection of car sharing station under picture fuzzy environment. Sustain Cities Soc 53:101873. https://doi.org/10.1016/j.scs.2019.101873
Liu P, Li Y (2019) An extended MULTIMOORA method for probabilistic linguistic multicriteria group decision-making based on prospect theory. Comput Ind Eng 136:528–545
Luo L, Zhang C, Liao H (2019) Distance-based intuitionistic multiplicative MULTIMOORA method integrating a novel weight-determining method for multiple criteria group decision making. Comput Ind Eng 131:82–98
Ma Z, Xu Z (2016) Symmetric Pythagorean fuzzy weighted geometric/averaging operators and their application in multi-criteria decision-making problems. Int J Intel Syst. 31(12):1198–1219
Mahmoud M, Ramadan M, Olabi A, Pullen K, Naher S (2020) A review of mechanical energy storage systems combined with wind and solar applications. Energy Convers Manag 210:112670. https://doi.org/10.1016/j.enconman.2020.112670
Medina P, Bizuayehu AW, Catalão JPS, Rodrigues EMG, Contreras J (2014) Electrical energy storage systems: technologies’ state-of-the-art, techno-economic benefits and applications analysis. In: 47th Hawaii international conference on system sciences, Waikoloa, HI, pp 2295–2304. https://doi.org/10.1109/HICSS.2014.290.
Mohler D, Sowder D (2017) Energy storage and the need for flexibility on the grid. renewable energy integration: practical management of variability, uncertainty, and flexibility in power grids, 2nd edn, Chapter 23, pp 309–316
Omrani H, Alizadeh A, Amini M (2020) A new approach based on BWM and MULTIMOORA methods for calculating semi-human development index: an application for provinces of Iran. Socio-Econ Plan Sci 70:100689. https://doi.org/10.1016/j.seps.2019.02.004
Peng X, Yang Y (2015) Some results for Pythagorean fuzzy sets. Int J Intell Syst 30(11):1133–1160
Peng X, Yang Y (2016) Pythagorean fuzzy Choquet integral based MABAC method for multi attribute group decision making. Int J Int Syst. 31(10):989–1020
Pérez-Domínguez L, Rodríguez-Picón LA, Alvarado-Iniesta A, David Luviano Cruz DL, Xu Z (2018) MOORA under Pythagorean fuzzy set for multiple criteria decision making. Complexity 2602376. https://doi.org/10.1155/2018/2602376
Rahimi S, Hafezalkotob A, Monavari SM, Hafezalkotob A, Rahimi R (2020) Sustainable landfill site selection for municipal solid waste based on a hybrid decision-making approach: fuzzy group BWM-MULTIMOORA-GIS. J Clean Prod 248:119186. https://doi.org/10.1016/j.jclepro.2019.119186
Sarbu I, Sebarchievici C (2018) A comprehensive review of thermal energy storage. Sustainability 10:191. https://doi.org/10.3390/su10010191
Shahzadi G, Akram M, Al-Kenani AN (2020) Decision-making approach under Pythagorean fuzzy Yager weighted operators. Mathematics 8:70. https://doi.org/10.3390/math8010070
Siksnelyte I, Zavadskas EK, Bausys R, Streimikiene D (2019) Implementation of EU energy policy priorities in the Baltic Sea Region countries: sustainability assessment based on neutrosophic MULTIMOORA method. Energy Policy 125:90–102
Smarandache F (1998) A unifying field in logics: neutrosophic logic. Neutrosophy, neutrosophic set, neutrosophic probability. American Research Press, Rehoboth
Souzangarzadeh H, Jahan A, Rezvani MJ et al (2020) Multi-objective optimization of cylindrical segmented tubes as energy absorbers under oblique crushes: D-optimal design and integration of MULTIMOORA with combinative weighting. Struct Multidisc Optim. https://doi.org/10.1007/s00158-020-02486-7
Tavana M, Shaabani A, Mohammadabadi SM, Varzganid N (2020) An integrated fuzzy AHP-fuzzy MULTIMOORA model for supply chain risk-benefit assessment and supplier selection. Int J Syst Sci: Oper Logist. https://doi.org/10.1080/23302674.2020.1737754
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: IEEE international conference on fuzzy systems, Jeju Island, Korea, 20–24 August 2009
Wang L, Garg H, Li N (2020) Pythagorean fuzzy interactive Hamacher power aggregation operators for assessment of express service quality with entropy weight. Soft Comput. https://doi.org/10.1007/s00500-020-05193-z
Wei G, Lu M (2018) Pythagorean fuzzy Maclaurin symmetric mean operators in multiple attribute decision making. Int J Intel Syst 33(5):1043–1070
Xian S, Liu Z, Gou X, Wan W (2020) Interval 2-tuple Pythagorean fuzzy linguistic MULTIMOORA method with CIA and their application to MCGDM. Int J Intell Syst 35(4):650–681
Yager RR (2013) Pythagorean fuzzy subsets. In: Proceedings of joint IFSA world congress and NAFIPS annual meeting, Edmonton, Canada, 24–28 June 2013, pp 57–61
Yager RR (2014) Pythagorean membership grades in multicriteria decision making. IEEE Trans Fuzzy Syst 22:958–965
Yager RR, Abbasov AM (2013) Pythagorean membership grades, complex numbers, and decision making. Int J Intell Syst 28(5):436–452
Yörükoğlu M, Aydın S (2020) Wind turbine selection by using MULTIMOORA method. Energy. https://doi.org/10.1007/s12667-020-00387-8
Zadeh LH (1965) Fuzzy sets. Inf. Control 8(3):338–353
Zadeh LH (1975) The concept of a linguistic variable and its applications to approximate reasoning. Inf Sci 8:199–249
Zafirakis DP (2010) Overview of energy storage technologies for renewable energy systems. In: Kaldellis JK (ed) Stand-alone and hybrid wind energy systems technology, energy storage and applications. Woodhead Publishing Series in Energy, pp 29–80
Zeng W, Li D, Yin Q (2018) Distance and similarity measures of Pythagorean fuzzy sets and their applications to multiple criteria group decision making. Int J Intell Syst 33(11):2236–2254
Zhang C, Chen C, Streimikiene D, Balezentis T (2019) Intuitionistic fuzzy MULTIMOORA approach for multi-criteria assessment of the energy storage technologies. Appl Soft Comput J 79:410–423
Zhang X (2016) A novel approach based on similarity measure for Pythagorean fuzzy multiple criteria group decision making. Int J Intel Syst. 31(6):593–611
Zhang X, Xu Z (2014) Extension of TOPSIS to multiple criteria decision making with Pythagorean fuzzy sets. Int J Intell Syst 29(12):1061–1078
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Sharaf, I.M. (2021). A Novel Pythagorean Fuzzy MULTIMOORA Applied to the Evaluation of Energy Storage Technologies. In: Garg, H. (eds) Pythagorean Fuzzy Sets. Springer, Singapore. https://doi.org/10.1007/978-981-16-1989-2_12
Download citation
DOI: https://doi.org/10.1007/978-981-16-1989-2_12
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-1988-5
Online ISBN: 978-981-16-1989-2
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)