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Selecting the most successfull recycling strategy over daily consumption products: application of q-Rung Orthopair Fuzzy Topsis method

Year 2024, Issue: 1, 61 - 68, 01.10.2024
https://doi.org/10.46810/tdfd.1423828

Abstract

Recycling is the process of collecting and reusing that helps the countries to achieve their sustainable development goals. This study, for the first time in the literature, considers the recycling of many daily consumption products as a decision-making problem with the q-rung orthopair fuzzy (q-ROF) approach. In Turkey, recycling initiatives are primarily led by the government and municipalities, involving either reprocessing in public facilities or collaboration with private enterprises. The research evaluates the effectiveness of recycling strategies, considering paper, plastic, textiles, batteries, frying oils, electronics, glass, and wood as alternative products. Criteria such as convertibility rate, resource usage for recycling, converted product lifespan, recycling process complexity, economic gain, product consumption rate, and trading opportunities are employed in the decision-making process. The q-rung orthopair fuzzy Technique for Order Preference by Similarity to Ideal Solution (q-ROFTOPSIS) method is applied to assess these criteria. Decision makers, comprising a recycling expert, a recycling business engineer, and an academician specializing in recycling studies, contribute to the evaluation. The study reveals electronic products as the most successful in recycling, while frying oils exhibit the least success.

References

  • Wibowo, S. & Deng, H. (2015). Multi-criteria group decision making for evaluating the performance of e-waste recycling programs under uncertainty, Waste Management. Vol.40, pp 127-135.Carlson BM. Human embryology and developmental biology. 4th ed. St. Louis: Mosby; 2009.
  • Huang, H. & Li, B. (2020). Optimization of WEEE recycling network for E-wastes based on discrete event simulation, Procedia CIRP. Vol. 90, pp 705-711.
  • Chakraborty, S. & Saha, AK. (2020). Selection of optimal lithiumion battery recycling process: A multi-criteria group decision making approach, Journal of Energy Storage. Vol. 55, Part B, 105557.
  • Su, J-P., Hung, M-L., Chao, C-W. & Ma, H., (2010). Applying multi-criteria decision-making to improve the waste reduction policy in Taiwan, Waste Management & Research. 28(1):20-28.
  • Tortorella, G., Silva, G., Campos, L.M.S., Pizzeta, C., Latosinski, A. & Soares, A. (2018). "Productivity improvement in solid waste recycling centres through lean implementation aided by multi-criteria decision analysis", Benchmarking: An International Journal. Vol. 25, No. 5, pp. 1480-1499.
  • Banar, M., Tulger, G. & Özkan, A., (2014). Plant Sıte Selectıon for Recyclıng Plants of Waste Electrıcal and Electronıc Equıpment in Turkey by Usıng Multı Crıterıa Decısıon Makıng Methods, Envıronmental Engıneerıng and Management Journal. Vol. 13, No. 1, pp. 163-172.
  • Zheng, C. & Zhou, Y., (2022). Multi-criteria Group Decision-Making Approach for Express Packaging Recycling Under Interval-Valued Fuzzy Information: Combining Objective and Subjective Compatibilities. Int. J. Fuzzy Syst. 24, 1112–1130 (2022).
  • Moro, C., (2023). Comparative Analysis of Multi-Criteria Decision Making and Life Cycle Assessment Methods for Sustainable Evaluation of Concrete Mixtures, Sustainability. 15, no. 17: 12746.
  • Hadipour, A., Rajaee, T., Hadipour, V. & Seidirad, S., (2016). Multi-criteria decision-making model for wastewater reuse application: a case study from Iran. Desalination and Water Treatment. 57:30, 13857-13864.
  • Ling, L., Anping, R. & Di, X., (2023). Proposal of a hybrid decision-making framework for the prioritization of express packaging recycling patterns, Environ Dev Sustain. 25, 2610–2647.
  • Koca, G. & Behdioglu, S., (2019). Multi-Criteria Decision Making in Green Supply Chain Management: An Example of Automotive Main Industry, Eskısehır Osmangazı Unıversıty Journal of Economıcs and Admınıstratıve Scıences. Vol. 14(3), pp. 675-698.
  • Stallkamp, C., Steins, J., Ruck, M., Volk, R., & Schultmann, F., (2022). Designing a Recycling Network for the Circular Economy of Plastics with Different Multi-Criteria Optimization Approaches, Sustainability. 14, no. 17: 10913.
  • Makarichi, L., Techato, K. & Jutidamrongphan, W., (2018). Material flow analysis as a support tool for multi-criteria analysis in solid waste management decision-making, Resources, Conservation and Recycling. Vol. 139, pp. 351-365.
  • Hanan, D., Burnley, S. & Cooke, D., (2023). A multi-criteria decision analysis assessment of waste paper management options, Waste Management. Vol. 33(3), pp. 566-573.
  • Bhuyan, A., Tripathy, A., Padhy, R. K. & Gautam, A., (2022). Evaluating the lithium-ion battery recycling industry in an emerging economy: A multi-stakeholder and multi-criteria decision-making approach, Journal of Cleaner Production. Vol. 331, 130007.
  • Dinçer, H. & Yüksel, S., (2023). Assessing the risk management-based impact relation map of nuclear energy system investments using the golden cut and bipolar q-ROF hybrid decision making model, Progress in Nuclear Energy. Vol. 165, 104911.
  • Seikh, M., R. & Mandal, U., (2023). q-Rung Orthopair Fuzzy Archimedean Aggregation Operators: Application in the Site Selection for Software Operating Unit. Symmetry 15, no. 9: 1680.
  • Oraya, A., F., Hana, A., C-T., Luciano, R., Patadlas, A., Baguio, I., Aro, L., J., Maturan, F. & Ocampo, L., (2023). An Integrated Multicriteria Sorting Methodology with q-Rung Orthopair Fuzzy Sets for Evaluating the Impacts of Delays on Residential Construction ProjectS. Axioms 12, no. 8: 735.
  • Khan, R., M., Ullah, K., Karamti, H., Khan, Q. & Mahmood, T., (2023). Multi-attribute group decision-making based on q-rung orthopair fuzzy Aczel–Alsina power aggregation operators, Engineering Applications of Artificial Intelligence. Vol. 126, Part A, 106629.
  • Naz, S., Akram, M., Davvaz, B. & Saadat A., (2023). A new decision-making framework for selecting the river crossing project under dual hesitant q-rung orthopair fuzzy 2-tuple linguistic environment, Soft Computing. Vol. 27(17), pp. 12021–12047.
  • Erdebilli, B., Gecer, E., Yılmaz, İ., Aksoy, T., Hacıoglu, Ü., Dinçer, H. & Yüksel. S., (2023). Q-ROF Fuzzy TOPSIS and VIKOR Methods for the Selection of Sustainable Private Health Insurance Policie, Sustainability. Vol.15, No. 12: 9229
  • Aytekin, A., Okoth, B., O., Korucuk, S., Mishra, R., A., Memiş, S., Karamaşa, Ç. & Tirkolaee, B., E., (2023). Critical success factors of lean six sigma to select the most ideal critical business process using q-ROF CRITIC-ARAS technique: Case study of food business, Expert Systems with Applications. Vol. 224, 120057.
  • Pinar, A. & Boran, F.E., (2020). A q-rung orthopair fuzzy multi-criteria group decision making method for supplier selection based on a novel distance measure, Int. J. Mach. Learn. & Cyber. 11, 1749–1780.
  • Alkan, N. & Kahraman, C., (2021). Evaluation of government strategies against COVID-19 pandemic using q-rung orthopair fuzzy TOPSIS method, Applied Soft Computing. Vol. 110, 107653.
  • Mishra, A.R. & Rani, P., (2023). A q-rung orthopair fuzzy ARAS method based on entropy and discrimination measures: an application of sustainable recycling partner selection, J Ambient Intell Human Comput 14, 6897–6918.
  • Yang, Z. & Chang, J., (2021). A multi-attribute decision-making-based site selection assessment algorithm for garbage disposal plant using interval q-rung orthopair fuzzy power Muirhead mean operator, Environmental Research. Vol. 193, 110385.
  • Pınar, A., Daneshvar, B., R. & Özdemir, S. Y., (2021). q-Rung Orthopair Fuzzy TOPSIS Method for Green Supplier Selection Problem, Sustainability. Vol. 13, No. 2: 985.
  • Zadeh, L.A. (1965). Fuzzy Sets, Information Control. Vol. 8, 338-353.
  • Atanassov, K.T. (1999). Intuitionistic Fuzzy Sets. In: Intuitionistic Fuzzy Sets. Studies in Fuzziness and Soft Computing, vol 35. Physica, Heidelberg.
  • Yager, R.R. (2016). Properties and Applications of Pythagorean Fuzzy Sets. In: Angelov, P., Sotirov, S. (eds) Imprecision and Uncertainty in Information Representation and Processing. Studies in Fuzziness and Soft Computing, vol 332. Springer, Cham. https://doi.org/10.1007/978-3-319-26302-1_9
Year 2024, Issue: 1, 61 - 68, 01.10.2024
https://doi.org/10.46810/tdfd.1423828

Abstract

References

  • Wibowo, S. & Deng, H. (2015). Multi-criteria group decision making for evaluating the performance of e-waste recycling programs under uncertainty, Waste Management. Vol.40, pp 127-135.Carlson BM. Human embryology and developmental biology. 4th ed. St. Louis: Mosby; 2009.
  • Huang, H. & Li, B. (2020). Optimization of WEEE recycling network for E-wastes based on discrete event simulation, Procedia CIRP. Vol. 90, pp 705-711.
  • Chakraborty, S. & Saha, AK. (2020). Selection of optimal lithiumion battery recycling process: A multi-criteria group decision making approach, Journal of Energy Storage. Vol. 55, Part B, 105557.
  • Su, J-P., Hung, M-L., Chao, C-W. & Ma, H., (2010). Applying multi-criteria decision-making to improve the waste reduction policy in Taiwan, Waste Management & Research. 28(1):20-28.
  • Tortorella, G., Silva, G., Campos, L.M.S., Pizzeta, C., Latosinski, A. & Soares, A. (2018). "Productivity improvement in solid waste recycling centres through lean implementation aided by multi-criteria decision analysis", Benchmarking: An International Journal. Vol. 25, No. 5, pp. 1480-1499.
  • Banar, M., Tulger, G. & Özkan, A., (2014). Plant Sıte Selectıon for Recyclıng Plants of Waste Electrıcal and Electronıc Equıpment in Turkey by Usıng Multı Crıterıa Decısıon Makıng Methods, Envıronmental Engıneerıng and Management Journal. Vol. 13, No. 1, pp. 163-172.
  • Zheng, C. & Zhou, Y., (2022). Multi-criteria Group Decision-Making Approach for Express Packaging Recycling Under Interval-Valued Fuzzy Information: Combining Objective and Subjective Compatibilities. Int. J. Fuzzy Syst. 24, 1112–1130 (2022).
  • Moro, C., (2023). Comparative Analysis of Multi-Criteria Decision Making and Life Cycle Assessment Methods for Sustainable Evaluation of Concrete Mixtures, Sustainability. 15, no. 17: 12746.
  • Hadipour, A., Rajaee, T., Hadipour, V. & Seidirad, S., (2016). Multi-criteria decision-making model for wastewater reuse application: a case study from Iran. Desalination and Water Treatment. 57:30, 13857-13864.
  • Ling, L., Anping, R. & Di, X., (2023). Proposal of a hybrid decision-making framework for the prioritization of express packaging recycling patterns, Environ Dev Sustain. 25, 2610–2647.
  • Koca, G. & Behdioglu, S., (2019). Multi-Criteria Decision Making in Green Supply Chain Management: An Example of Automotive Main Industry, Eskısehır Osmangazı Unıversıty Journal of Economıcs and Admınıstratıve Scıences. Vol. 14(3), pp. 675-698.
  • Stallkamp, C., Steins, J., Ruck, M., Volk, R., & Schultmann, F., (2022). Designing a Recycling Network for the Circular Economy of Plastics with Different Multi-Criteria Optimization Approaches, Sustainability. 14, no. 17: 10913.
  • Makarichi, L., Techato, K. & Jutidamrongphan, W., (2018). Material flow analysis as a support tool for multi-criteria analysis in solid waste management decision-making, Resources, Conservation and Recycling. Vol. 139, pp. 351-365.
  • Hanan, D., Burnley, S. & Cooke, D., (2023). A multi-criteria decision analysis assessment of waste paper management options, Waste Management. Vol. 33(3), pp. 566-573.
  • Bhuyan, A., Tripathy, A., Padhy, R. K. & Gautam, A., (2022). Evaluating the lithium-ion battery recycling industry in an emerging economy: A multi-stakeholder and multi-criteria decision-making approach, Journal of Cleaner Production. Vol. 331, 130007.
  • Dinçer, H. & Yüksel, S., (2023). Assessing the risk management-based impact relation map of nuclear energy system investments using the golden cut and bipolar q-ROF hybrid decision making model, Progress in Nuclear Energy. Vol. 165, 104911.
  • Seikh, M., R. & Mandal, U., (2023). q-Rung Orthopair Fuzzy Archimedean Aggregation Operators: Application in the Site Selection for Software Operating Unit. Symmetry 15, no. 9: 1680.
  • Oraya, A., F., Hana, A., C-T., Luciano, R., Patadlas, A., Baguio, I., Aro, L., J., Maturan, F. & Ocampo, L., (2023). An Integrated Multicriteria Sorting Methodology with q-Rung Orthopair Fuzzy Sets for Evaluating the Impacts of Delays on Residential Construction ProjectS. Axioms 12, no. 8: 735.
  • Khan, R., M., Ullah, K., Karamti, H., Khan, Q. & Mahmood, T., (2023). Multi-attribute group decision-making based on q-rung orthopair fuzzy Aczel–Alsina power aggregation operators, Engineering Applications of Artificial Intelligence. Vol. 126, Part A, 106629.
  • Naz, S., Akram, M., Davvaz, B. & Saadat A., (2023). A new decision-making framework for selecting the river crossing project under dual hesitant q-rung orthopair fuzzy 2-tuple linguistic environment, Soft Computing. Vol. 27(17), pp. 12021–12047.
  • Erdebilli, B., Gecer, E., Yılmaz, İ., Aksoy, T., Hacıoglu, Ü., Dinçer, H. & Yüksel. S., (2023). Q-ROF Fuzzy TOPSIS and VIKOR Methods for the Selection of Sustainable Private Health Insurance Policie, Sustainability. Vol.15, No. 12: 9229
  • Aytekin, A., Okoth, B., O., Korucuk, S., Mishra, R., A., Memiş, S., Karamaşa, Ç. & Tirkolaee, B., E., (2023). Critical success factors of lean six sigma to select the most ideal critical business process using q-ROF CRITIC-ARAS technique: Case study of food business, Expert Systems with Applications. Vol. 224, 120057.
  • Pinar, A. & Boran, F.E., (2020). A q-rung orthopair fuzzy multi-criteria group decision making method for supplier selection based on a novel distance measure, Int. J. Mach. Learn. & Cyber. 11, 1749–1780.
  • Alkan, N. & Kahraman, C., (2021). Evaluation of government strategies against COVID-19 pandemic using q-rung orthopair fuzzy TOPSIS method, Applied Soft Computing. Vol. 110, 107653.
  • Mishra, A.R. & Rani, P., (2023). A q-rung orthopair fuzzy ARAS method based on entropy and discrimination measures: an application of sustainable recycling partner selection, J Ambient Intell Human Comput 14, 6897–6918.
  • Yang, Z. & Chang, J., (2021). A multi-attribute decision-making-based site selection assessment algorithm for garbage disposal plant using interval q-rung orthopair fuzzy power Muirhead mean operator, Environmental Research. Vol. 193, 110385.
  • Pınar, A., Daneshvar, B., R. & Özdemir, S. Y., (2021). q-Rung Orthopair Fuzzy TOPSIS Method for Green Supplier Selection Problem, Sustainability. Vol. 13, No. 2: 985.
  • Zadeh, L.A. (1965). Fuzzy Sets, Information Control. Vol. 8, 338-353.
  • Atanassov, K.T. (1999). Intuitionistic Fuzzy Sets. In: Intuitionistic Fuzzy Sets. Studies in Fuzziness and Soft Computing, vol 35. Physica, Heidelberg.
  • Yager, R.R. (2016). Properties and Applications of Pythagorean Fuzzy Sets. In: Angelov, P., Sotirov, S. (eds) Imprecision and Uncertainty in Information Representation and Processing. Studies in Fuzziness and Soft Computing, vol 332. Springer, Cham. https://doi.org/10.1007/978-3-319-26302-1_9
There are 30 citations in total.

Details

Primary Language English
Subjects Decision Support and Group Support Systems, Waste Management, Reduction, Reuse and Recycling
Journal Section Articles
Authors

Sinan Öztaş 0000-0002-9630-6586

Publication Date October 1, 2024
Submission Date January 22, 2024
Acceptance Date April 17, 2024
Published in Issue Year 2024 Issue: 1

Cite

APA Öztaş, S. (2024). Selecting the most successfull recycling strategy over daily consumption products: application of q-Rung Orthopair Fuzzy Topsis method. Türk Doğa Ve Fen Dergisi(1), 61-68. https://doi.org/10.46810/tdfd.1423828
AMA Öztaş S. Selecting the most successfull recycling strategy over daily consumption products: application of q-Rung Orthopair Fuzzy Topsis method. TJNS. October 2024;(1):61-68. doi:10.46810/tdfd.1423828
Chicago Öztaş, Sinan. “Selecting the Most Successfull Recycling Strategy over Daily Consumption Products: Application of Q-Rung Orthopair Fuzzy Topsis Method”. Türk Doğa Ve Fen Dergisi, no. 1 (October 2024): 61-68. https://doi.org/10.46810/tdfd.1423828.
EndNote Öztaş S (October 1, 2024) Selecting the most successfull recycling strategy over daily consumption products: application of q-Rung Orthopair Fuzzy Topsis method. Türk Doğa ve Fen Dergisi 1 61–68.
IEEE S. Öztaş, “Selecting the most successfull recycling strategy over daily consumption products: application of q-Rung Orthopair Fuzzy Topsis method”, TJNS, no. 1, pp. 61–68, October 2024, doi: 10.46810/tdfd.1423828.
ISNAD Öztaş, Sinan. “Selecting the Most Successfull Recycling Strategy over Daily Consumption Products: Application of Q-Rung Orthopair Fuzzy Topsis Method”. Türk Doğa ve Fen Dergisi 1 (October 2024), 61-68. https://doi.org/10.46810/tdfd.1423828.
JAMA Öztaş S. Selecting the most successfull recycling strategy over daily consumption products: application of q-Rung Orthopair Fuzzy Topsis method. TJNS. 2024;:61–68.
MLA Öztaş, Sinan. “Selecting the Most Successfull Recycling Strategy over Daily Consumption Products: Application of Q-Rung Orthopair Fuzzy Topsis Method”. Türk Doğa Ve Fen Dergisi, no. 1, 2024, pp. 61-68, doi:10.46810/tdfd.1423828.
Vancouver Öztaş S. Selecting the most successfull recycling strategy over daily consumption products: application of q-Rung Orthopair Fuzzy Topsis method. TJNS. 2024(1):61-8.

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