Positive impact of waste management strategies and decision analysis with intuitionistic Fuzzy Sugeno-Weber aggregation operators

Abrar  Hussain; Kifayat  Ullah; Shi  Yin; Yong  Deng; Dragan Pamucar; Vladimir  Simic

doi:10.5269/bspm.79085

Abrar Hussain Department of Mathematics, Riphah International University (Lahore Campus), 54000, Lahore, Pakistan
Kifayat Ullah Department of Mathematics, Riphah International University (Lahore Campus), 54000, Lahore, Pakistan. Department of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai 602105, Tamil Nadu, India.
Shi Yin College of Economics and Management, Hebei Agricultural University, Baoding, China
Yong Deng Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu, 610054, China
Dragan Pamucar Department of Operations Research and Statistics, Faculty of Organizational Sciences,University of Belgrade, Belgrade,Serbia
Vladimir Simic Széchenyi István University, Györ, Hungary Department of Computer Science and Engineering,College of Informatics, Korea University, Seoul 02841,Republic of Korea

Abstract

Waste management is a crucial and significant subject that has gained much attention globally because it has several environmental, social, financial and economic implications. Solid waste management is a very challenging task for clean urban and rural societies. We studied some reliable strategies for handling the waste materials and garbage produced by people. To serve this purpose, an intuitionistic fuzzy set (IFS) is a well-known model used for modeling and processing unpredictable information and providing accurate approximated results in the decision-making process. Power average operators allow the interrelationship of the input arguments and deal with uncertain information in complicated situations. This article expresses Sugeno-weber triangular norms under intuitionistic fuzzy (IF) information. We developed a class of new aggregation operators, including intuitionistic fuzzy Sugeno-Weber power-weighted average (IFSWPWA) and intuitionistic fuzzy Sugeno-Weber power-weighted geometric (IFSWPWG) operators. It is observed that both the newly proposed operators satisfy the properties of aggregation. The multi-criteria decision-making (MCDM) problem is proposed to evaluate real-life applications and numerical examples. An experimental case study under the system of waste materials is considered in the article to reveal the intensity and applicability of derived approaches. The comparison analysis and sensitivity analysis show the significance of our proposed work.

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Author Biographies

Kifayat Ullah, Department of Mathematics, Riphah International University (Lahore Campus), 54000, Lahore, Pakistan. Department of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai 602105, Tamil Nadu, India.

Department of Mathematics,
Riphah International University (Lahore Campus), 54000, Lahore,
Pakistan.
Department of Mathematics,
Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai
602105, Tamil Nadu,
India.

Dragan Pamucar, Department of Operations Research and Statistics, Faculty of Organizational Sciences,University of Belgrade, Belgrade,Serbia

Department of Operations Research and Statistics, Faculty of Organizational Sciences,
University of Belgrade, Belgrade,
Serbia
Faculty of Engineering,
Dogus University, Istanbul,
Türkiye.

Vladimir Simic , Széchenyi István University, Györ, Hungary Department of Computer Science and Engineering,College of Informatics, Korea University, Seoul 02841,Republic of Korea

Széchenyi István University, Györ, Hungary
Department of Computer Science and Engineering,
College of Informatics, Korea University, Seoul 02841,
Republic of Korea

References

Katrancı, A., Kundakcı, N., & Arman, K., Fuzzy SIWEC and Fuzzy RAWEC Methods for Sustainable Waste Disposal Technology Selection. Spectrum of Operational Research, 3(1), 87–102, (2025) doi:10.31181/sor31202633.

Ike, C.C.; Ezeibe, C.C.; Anijiofor, S.C.; Daud, N.N.N. Solid Waste Management in Nigeria: Problems, Prospects, and Policies Available online: https://www.ingentaconnect.com/content/jswt/jswt/2018/00000044/00000002/art00008 (accessed on 19 December 2023).

Ugwu, C.O.; Ozoegwu, C.G.; Ozor, P.A. Solid Waste Quantification and Characterization in University of Nigeria, Nsukka Campus, and Recommendations for Sustainable Management. Heliyon, 6. (2020)

Ozekenci, E. K., A Multi-Criteria Framework for Economic Decision Support in Urban Sustainability: Comparative Insights from European Cities. International Journal of Economic Sciences, 14(1), 162–181, (2025) doi:10.31181/ijes1412025188.

Monzeli, A., Daneshian, B., Tohidi, G., Sanei, M., & Razaveian, S., Improving Hospital Efficiency and Economic Performance: A DEA Approach with Undesirable Factors in Tehran Emergency Wards. International Journal of Economic Sciences, 14(1), 90–107, (2025) doi:10.31181/ijes1412025174.

Coker, A.O.; Achi, C.G.; Sridhar, M.K.C.; Donnett, C.J. Solid Waste Management Practices at a Private Institution of Higher Learning in Nigeria. Procedia Environ. Sci. 35, 28–39. (2016)

Mondal, S., Goswami, S. S., Gupta, K. K., & Sahoo, S. K., Synergistic Effects of Lean Manufacturing and Digitalization on Operational Effectiveness: A Comprehensive Review. Spectrum of Decision Making and Applications, 3(1), 21–39, (2025) doi:10.31181/sdmap31202634.

Adeleke, O.; Akinlabi, S.; Jen, T.-C.; Dunmade, I. A Machine Learning Approach for Investigating the Impact of Seasonal Variation on Physical Composition of Municipal Solid Waste. J. Reliab. Intell. Environ. 9, 99–118, 2023). doi:10.1007/s40860-021-00168-9.

Podlasek, A.; Vaverkova, M.D.; Koda, E.; Jakimiuk, A.; Barroso, P.M. Characteristics and Pollution Potential of Leachate from Municipal Solid Waste Landfills: Practical Examples from Poland and the Czech Republic and a Comprehensive Evaluation in a Global Context. J. Environ. Manage., 332, 117328, (2023).

Dagıstanlı, H. A., Prioritizing Design Criteria for Unmanned Helicopter Systems under Uncertainty using Fuzzy Best Worst Method Approach. Journal of Intelligent Decision Making and Granular Computing, 1(1), 1–12, (2025) doi:10.31181/jidmgc1120251.

Kumar, R., & Pamucar, D. (2025). A Comprehensive and Systematic Review of Multi-Criteria Decision-Making (MCDM) Methods to Solve Decision-Making Problems: Two Decades from 2004 to 2024. Spectrum of Decision Making and Applications, 2(1), 178-197. https://doi.org/10.31181/sdmap21202524

Ravichandran, K. S., Double Decker Decision Framework with Fuzzy Data for Multi-Attribute Decision-Making. Management Science Advances, 2(1), 214–222, (2025) doi:10.31181/msa2120259.

Sarfraz, M., & Gul, R., Multi-Attribute Decision-Analytic Approach based on Spherical Fuzzy Rough Schweizer-Sklar Aggregation Operators with Applications in Agricultural Management Systems. Management Science Advances, 2(1), 260–281, (2025) doi:10.31181/msa21202520.

Palanikumar, M., & Kausar, N., Research on the Redefined Square Root Interval-valued Normal Pythagorean Fuzzy Multi-Attribute Decision-Making Model Based on Aggregation Operators. Spectrum of Operational Research, 4(1), 1–18, (2025) doi:10.31181/sor58.

Zadeh, L.A. Fuzzy Sets. Inf. Control, 8, 338–353, (1965). doi:10.1016/S0019-9958(65)90241-X.

Adlassnig, K.-P. Fuzzy Set Theory in Medical Diagnosis. IEEE Trans. Syst. Man Cybern., 16, 260–265, (1986).

Atanassov, K.T. Intuitionistic Fuzzy Sets. Fuzzy Sets Syst., 20, 87–96, (1986). doi:10.1016/S0165-0114(86)80034-3.

Atanassov, K.T. Two Theorems for Intuitionistic Fuzzy Sets. Fuzzy Sets Syst., 110, 267–269. (2000).

Atanassov, K.T. More on Intuitionistic Fuzzy Sets. Fuzzy Sets Syst. 33, 37–45, (1989). doi:10.1016/0165-0114(89)90215-7.

Ahmmad, J.; Mahmood, T.; Mehmood, N.; Urawong, K.; Chinram, R. Intuitionistic Fuzzy Rough Aczel-Alsina Average Aggregation Operators and Their Applications in Medical Diagnoses. Symmetry, 14, 2537, (2022).

Albaity, M.; Mahmood, T.; Ali, Z. Impact of Machine Learning and Artificial Intelligence in Business Based on Intuitionistic Fuzzy Soft WASPAS Method. Mathematics, 11, 1453, (2023). doi:10.3390/math11061453.

Alcantud, J.C.R.; Khameneh, A.Z.; Kilicman, A. Aggregation of Infinite Chains of Intuitionistic Fuzzy Sets and Their Application to Choices with Temporal Intuitionistic Fuzzy Information. Inf. Sci., 514, 106–117, (2020). doi:10.1016/j.ins.2019.12.008.

Wang, H., & Liu, J., Some Spherical Uncertain Linguistic Aggregation Operators and their Application in MultiAttribute Decision-Making. Journal of Intelligent Decision Making and Granular Computing, 1(1), 106–126, (2025) doi:10.31181/jidmgc11202511.

Sarkar, A.; Moslem, S.; Esztergar-Kiss, D.; Akram, M.; Jin, L.; Senapati, T. A Hybrid Approach Based on Dual Hesitant Q-Rung Orthopair Fuzzy Frank Power Partitioned Heronian Mean Aggregation Operators for Estimating Sustainable Urban Transport Solutions. Eng. Appl. Artif. Intell. 2023, 124, 106505, doi:10.1016/j.engappai.2023.106505.

Senapati, T.; Simic, V.; Saha, A.; Dobrodolac, M.; Rong, Y.; Tirkolaee, E.B. Intuitionistic Fuzzy Power Aczel-Alsina Model for Prioritization of Sustainable Transportation Sharing Practices. Eng. Appl. Artif. Intell., 119, 105716, (2023).

Hussain, A.; Ullah, K.; Alshahrani, M.N.; Yang, M.-S.; Pamucar, D. Novel Aczel–Alsina Operators for Pythagorean Fuzz]y Sets with Application in Multi-Attribute Decision Making. Symmetry, 14, 940, (2022).

Garg, H. Intuitionistic Fuzzy Hamacher Aggregation Operators with Entropy Weight and Their Applications to MultiCriteria Decision-Making Problems. Iran. J. Sci. Technol. Trans. Electr. Eng., 43, 597–613, (2019).

Zhou, Q.; Mo, H.; Deng, Y. A New Divergence Measure of Pythagorean Fuzzy Sets Based on Belief Function and Its Application in Medical Diagnosis. Mathematics, 8, 142, (2020). doi:10.3390/math8010142.

Garg, H.; Chen, S.-M. Multiattribute Group Decision Making Based on Neutrality Aggregation Operators of Q-Rung Orthopair Fuzzy Sets. Inf. Sci., 517, 427–447, (2020). doi:10.1016/j.ins.2019.11.035.

Arora, R.; Garg, H. Group Decision-Making Method Based on Prioritized Linguistic Intuitionistic Fuzzy Aggregation Operators and Its Fundamental Properties. Comput. Appl. Math., 38, 36, (2019). doi:10.1007/s40314-019-0764-1.

Akram, M.; Bibi, R. Multi-Criteria Group Decision-Making Based on an Integrated PROMETHEE Approach with 2-Tuple Linguistic Fermatean Fuzzy Sets. Granul. Comput., 1–25, (2023).

Sarkar, A.; Deb, N.; Biswas, A. Weighted Dual Hesitant Q-Rung Orthopair Fuzzy Sets and Their Application in Multicriteria Group Decision Making Based on Hamacher Operations. Comput. Appl. Math. 2023, 42, 40.

Fei, L.; Deng, Y. Multi-Criteria Decision Making in Pythagorean Fuzzy Environment. Appl. Intell. 2020, 50, 537–561.

Hussain, A.; Ullah, K.; Ali, Z.; Moslem, S.; Senapati, T. An Enhanced Physical Education Evaluation Algorithm for Higher Education Using Interval Valued Fermatean Fuzzy Information. Socioecon. Plann. Sci. 2025, 102280, doi:10.1016/j.seps.2025.102280.

Mahmood, T.; Waqas, H.M.; Ali, Z.; Ullah, K.; Pamucar, D. Frank Aggregation Operators and Analytic Hierarchy Process Based on Interval-Valued Picture Fuzzy Sets and Their Applications. Int. J. Intell. Syst., 36, 7925–7962,(2021).

Deng, J.; Deng, Y. Information Volume of Fuzzy Membership Function. Int. J. Comput. Commun. Control, 16, (2021).

Liu, P.; Gao, H. Some Intuitionistic Fuzzy Power Bonferroni Mean Operators in the Framework of Dempster–Shafer Theory and Their Application to Multicriteria Decision Making. Appl. Soft Comput., 85, 105790, (2019).

Ali, J.; Naeem, M. Complex Q-Rung Orthopair Fuzzy Aczel–Alsina Aggregation Operators and Its Application to Multiple Criteria Decision-Making with Unknown Weight Information. IEEE Access, 10, 85315–85342, (2022).

Hayat, K.; Raja, M.S.; Lughofer, E.; Yaqoob, N. New Group-Based Generalized Interval-Valued q-Rung Orthopair Fuzzy Soft Aggregation Operators and Their Applications in Sports Decision-Making Problems. Comput. Appl. Math., 42, 4, (2023).

Hussain, A.; Wang, H.; Ullah, K.; Pamucar, D. Novel Intuitionistic Fuzzy Aczel Alsina Hamy Mean Operators and Their Applications in the Assessment of Construction Material. Complex Intell. Syst., 1–26, (2023).

Juan, W.; Qiang, L. Interval-Valued Hesitant Fuzzy Linguistic Multiattribute Decision-Making Method Based on ThreeParameter Heronian Mean Operators. J. Math. 2021, e3634895, (2021). doi:10.1155/2021/3634895.

Sugeno, M. Theory of Fuzzy Integrals and Its Applications. Dr. Thesis Tokyo Inst. Technol. (1974).

Weber, S. A General Concept of Fuzzy Connectives, Negations and Implications Based on t-Norms and t-Conorms. Fuzzy Sets Syst., 11, 115–134,(1983).

Hussain, A., & Ullah, K., An Intelligent Decision Support System for Spherical Fuzzy Sugeno-Weber Aggregation Operators and Real-Life Applications. Spectrum of Mechanical Engineering and Operational Research, 1(1), 177–188, (2024) doi:10.31181/smeor11202415.

Ghodousian, A.; Ahmadi, A.; Dehghani, A. Solving a Non-Convex Non-Linear Optimization Problem Constrained by Fuzzy Relational Equations and Sugeno-Weber Family of t-Norms. J. Algorithms Comput., 49, 63–101, (2017).

Murofushi, T.; Sugeno, M. Fuzzy T-Conorm Integral with Respect to Fuzzy Measures: Generalization of Sugeno Integral and Choquet Integral. Fuzzy Sets Syst., 42, 57–71, (1991).

Sarkar, A.; Senapati, T.; Jin, L.; Mesiar, R.; Biswas, A.; Yager, R.R. Sugeno–Weber Triangular Norm-Based Aggregation Operators Under T-Spherical Fuzzy Hypersoft Context. Inf. Sci., 119305,(2023).

Hussain, A.; Ullah, K.; Pamucar, D.; Haleemzai, I.; Tatic, D. Assessment of Solar Panel Using Multiattribute DecisionMaking Approach Based on Intuitionistic Fuzzy Aczel Alsina Heronian Mean Operator. Int. J. Intell. Syst., (2023).

Senapati, T.; Chen, G.; Mesiar, R.; Yager, R.R. Intuitionistic Fuzzy Geometric Aggregation Operators in the Framework of Aczel-Alsina Triangular Norms and Their Application to Multiple Attribute Decision Making. Expert Syst. Appl., 212, 118832, (2023).

Yager, R.R. The Power Average Operator. IEEE Trans. Syst. Man Cybern. - Part Syst. Hum., 31, 724–731,(2001). doi:10.1109/3468.983429.

Mishra, A. R., Rani, P., Pamucar, D., Alshamrani, A. M., & Alrasheedi, A. F., Intuitionistic Fuzzy MACONT Method for Logistics 4.0 Based Circular Economy Interested Regions Assessment in the Agri-Food Sector. Facta Universitatis, Series: Mechanical Engineering, 22(4), 407–432, (2024) doi:10.22190/FUME241001052M.

Sandra, M., Narayanamoorthy, S., Suvitha, K., Pamucar, D., & Kang, D., Optimizing Non-Invasive Remote Sensing for Geothermal Exploration with T-Spherical Dual Hesitant Fuzzy Decision Model. Facta Universitatis, Series: Mechanical Engineering, 23(6), 533–554, (2025) doi:10.22190/FUME241116016S.

Ogwueleka, T. Municipal Solid Waste Characteristics and Management in Nigeria. J. Environ. Health Sci. Eng., 6, 173–180,(2009).

Xu, Z. Intuitionistic Fuzzy Aggregation Operators. IEEE Trans. Fuzzy Syst., 15, 1179–1187,(2007).

Seikh, M.R.; Mandal, U. Intuitionistic Fuzzy Dombi Aggregation Operators and Their Application to Multiple Attribute Decision-Making. Granul. Comput., 6, 473–488,(2021).

Senapati, T.; Chen, G.; Yager, R.R. Aczel–Alsina Aggregation Operators and Their Application to Intuitionistic Fuzzy Multiple Attribute Decision Making. Int. J. Intell. Syst., 37, 1529–1551,(2022).

Hussain, A.; Ullah, K.; Ahmad, J.; Karamti, H.; Pamucar, D.; Wang, H., Applications of the Multiattribute DecisionMaking for the Development of the Tourism Industry Using Complex Intuitionistic Fuzzy Hamy Mean Operators. Comput. Intell. Neurosci. (2022)