Research Article
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An Integrated PIPRECIA and COPRAS Method under Fuzzy Environment: A Case of Truck Tractor Selection

Year 2021, Volume: 9 Issue: 2, 269 - 298, 31.12.2021
https://doi.org/10.17093/alphanumeric.1005970

Abstract

Selecting the right truck tractor is critical for logistics companies involved in road freight transportation. The fact that having many conflicting criteria and many alternatives complicates the decision-making process for the decision-makers (DMs). The determination of the criteria that are effective in the selection of truck tractors and then the evaluation of the alternatives are the main objectives of this study. In this context, a hybrid Multi-Criteria Decision-Making (MCDM) model composed of Fuzzy PIPRECIA (F-PIPRECIA) and Fuzzy COPRAS (F-COPRAS) methods is proposed to be used in the selection of truck tractors. In the related literature, no studies that applied F-PIPRECIA and F-COPRAS together to determine the best truck tractor have been published yet. In this regard, this study is thought to contribute to the literature both in terms of the methods used and the application of truck tractor selection. Moreover, the findings of this study will pave the way for those who conduct academic studies and the authorities of companies involved in road transport in the logistics sector.

References

  • Alkan, Ö., & Albayrak, Ö. K. (2020). Ranking of renewable energy sources for regions in Turkey by fuzzy entropy based fuzzy COPRAS and fuzzy MULTIMOORA. Renewable Energy, 162, 712-726. https://doi.org/10.1016/j.renene.2020.08.062
  • Ansari, Z. N., Kant, R., & Shankar, R. (2020). Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach. International Journal of Sustainable Engineering, 13(6), 473-494. https://doi.org/10.1080/19397038.2020.1758973
  • Başaran, B., & Çakir, S. (2021). Evaluation of food safety and halal criteria in supplier selection: an application in food sector with fuzzy COPRAS method. International Food Research Journal, 28(3), 576-585. ISSN: 19854668
  • Baykaşoğlu, A. (2010). Çok kriterli TIR çekici seçimi. LODER Lojistik Dergisi, 14, 32-36.
  • Baykasoğlu, A., & Golcuk, I. (2014). Çok kriterli tır çekici seçiminde bulanık integral yaklaşımı. 3. Ulusal Lojistik ve Tedarik Zinciri Kongresi, Karadeniz Teknik Üniversitesi, 15-17 Mayıs 2014, Trabzon, 776-786.
  • Baykaşoğlu, A., Dereli, T., Altun, K., (2011). Kullanılmış tır çekici seşimi: pratik bir karar destek yaklaşımı EVEN-SWAP. Lojistik, 19, 18-22
  • Baykaşoğlu, A., Kaplanoğlu, V., Durmuşoğlu, Z. D., & Şahin, C. (2013). Integrating fuzzy DEMATEL and fuzzy hierarchical TOPSIS methods for truck selection. Expert Systems with Applications, 40(3), 899-907. https://doi.org/10.1016/j.eswa.2012.05.046
  • Blagojević, A., Kasalica, S., Stević, Ž., Tričković, G., & Pavelkić, V. (2021). Evaluation of safety degree at railway crossings in order to achieve sustainable traffic management: A novel integrated fuzzy MCDM model. Sustainability, 13(2), 832. DOI: 10.3390/su13020832
  • Blagojević, A., Stević, Ž., Marinković, D., Kasalica, S., & Rajilić, S. (2020). A novel entropy-fuzzy PIPRECIA-DEA model for safety evaluation of railway traffic. Symmetry, 12(9), 1479. doi:10.3390/sym12091479
  • Chakraborty, S., & Prasad, K. (2016). A QFD-based expert system for industrial truck selection in manufacturing organizations. Journal of Manufacturing Technology Management.
  • Chan, F. T., Jha, A., & Tiwari, M. K. (2016). Bi-objective optimization of three echelon supply chain involving truck selection and loading using NSGA-II with heuristics algorithm. Applied soft computing, 38, 978-987.
  • Đalić, I., Stević, Ž., Karamasa, C., & Puška, A. (2020). A novel integrated fuzzy PIPRECIA–interval rough SAW model: Green supplier selection. Decision Making: Applications in Management and Engineering, 3(1), 126-145. DOI: https://doi.org/10.31181/dmame2003114d
  • de Sousa Junior, W. T., Souza, M. J. F., Cabral, I. E., & Diniz, M. E. (2014). Multi-Criteria Decision Aid methodology applied to highway truck selection at a mining company. Rem: Revista Escola de Minas, 67(3), 285-290.
  • Dhiman, H. S., & Deb, D. (2020). Fuzzy TOPSIS and fuzzy COPRAS based multi-criteria decision making for hybrid wind farms. Energy, 202, 117755. https://doi.org/10.1016/j.energy.2020.117755
  • Doğan, E. M., Eren, M., & Çelik, K. (2017). Lojistik sektöründe ağır ticari araç seçimi problemine yönelik COPRAS-G yöntemi ile karar verme. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 19(1), 153-178.
  • Garg, R., Kumar, R., & Garg, S. (2019). MADM-based parametric selection and ranking of E-learning websites using fuzzy COPRAS. IEEE Transactions on Education, 62(1), 11-18. DOI: 10.1109/TE.2018.2814611
  • Görçün, Ö. F. (2019). Uluslararası Taşımacılık İşletmelerinin Çekici Araç Seçimlerinin Entegre AHP, Entropi ve TOPSIS Yöntemleri Kullanılarak Analizi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 21(3), 899-922. https://doi.org/10.32709/akusosbil.521611
  • Hasheminezhad, A., Hadadi, F., & Shirmohammadi, H. (2021). Investigation and prioritization of risk factors in the collision of two passenger trains based on fuzzy COPRAS and fuzzy DEMATEL methods. Soft Computing, 25, 4677-4697. https://doi.org/10.1007/s00500-020-05478-3
  • Khorasani, S. T. (2018). Green supplier evaluation by using the integrated fuzzy AHP model and fuzzy copras. Process Integration and Optimization for Sustainability, 2(1), 17-25. DOI: 10.1007/s41660-017-0027-9
  • Marković, V., Stajić, L., Stević, Ž., Mitrović, G., Novarlić, B., & Radojičić, Z. (2020). A novel integrated subjective-objective mcdm model for alternative ranking in order to achieve business excellence and sustainability. Symmetry, 12(1), 164. DOI: 10.3390/SYM12010164
  • Nedeljković, M., Puška, A., Doljanica, S., Virijević Jovanović, S., Brzaković, P., Stević, Ž., & Marinkovic, D. (2021). Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA–Fuzzy MABAC model. Plos one, 16(2), e0246857. https://doi.org/10.1371/journal.pone.0246857
  • Puška, A., Nedeljković, M., Hashemkhani Zolfani, S., & Pamučar, D. (2021). Application of interval fuzzy logic in selecting a sustainable supplier on the example of agricultural production. Symmetry, 13(5), 774. DOI: 10.3390/sym13050774
  • Roozbahani, A., Ghased, H., & Shahedany, M. H. (2020). Inter-basin water transfer planning with grey COPRAS and fuzzy COPRAS techniques: A case study in Iranian Central Plateau. Science of the Total Environment, 726, 138499. https://doi.org/10.1016/j.scitotenv.2020.138499
  • Shaikh, A., Singh, A., Ghose, D., & Shabbiruddin. (2020). Analysis and selection of optimum material to improvise braking system in automobiles using integrated Fuzzy-COPRAS methodology. International Journal of Management Science and Engineering Management, 15(4), 265-273. https://doi.org/10.1080/17509653.2020.1772895
  • Stanković, M., Stević, Ž., Das, D. K., Subotić, M., & Pamučar, D. (2020). A new fuzzy MARCOS method for road traffic risk analysis. Mathematics, 8(3), 457. DOI: 10.3390/MATH8030457
  • Stevic, Ž., Stjepanovic, Ž., Božickovic, Z., Das, D. K., & Stanujkic, D. (2018). Assessment of Conditions for Implementing Information Technology in a Warehouse System: A Novel Fuzzy PIPRECIA Method. Symmetry, 10 (586), 1-28. doi: 10.3390/sym10110586.
  • Tolga, A. C., & Durak, G. (2019). Evaluating innovation projects in air cargo sector with fuzzy COPRAS. In International Conference on Intelligent and Fuzzy Systems (pp. 702-710). Springer, Cham. DOI: 10.1007/978-3-030-23756-1_84
  • Tomašević, M., Lapuh, L., Stević, Ž., Stanujkić, D., & Karabašević, D. (2020). Evaluation of criteria for the implementation of high-performance computing (HPC) in Danube Region countries using fuzzy PIPRECIA method. Sustainability, 12(7), 3017. https://doi.org/10.3390/su12073017
  • Vesković, S., Milinković, S., Abramović, B., & Ljubaj, I. (2020). Determining criteria significance in selecting reach stackers by applying the fuzzy PIPRECIA method. Operational Research in Engineering Sciences: Theory and Applications, 3(1), 72-88. DOI: https://doi.org/10.31181/oresta2001072v
  • Yazdani, Morteza., Alidoosti, Ali., Zavadskas, Edmundas, K. (2011). Risk Analysis of Critical Infrastructures Using Fuzzy Copras, Economic Research-Ekonomska Istraživanja, 24:4, 27-40, DOI: 10.1080/1331677X.2011.11517478.
  • Zarbakhshnia, N., Soleimani, H., & Ghaderi, H. (2018). Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed fuzzy COPRAS in the presence of risk criteria. Applied Soft Computing, 65, 307-319. DOI: 10.1016/j.asoc.2018.01.023
Year 2021, Volume: 9 Issue: 2, 269 - 298, 31.12.2021
https://doi.org/10.17093/alphanumeric.1005970

Abstract

References

  • Alkan, Ö., & Albayrak, Ö. K. (2020). Ranking of renewable energy sources for regions in Turkey by fuzzy entropy based fuzzy COPRAS and fuzzy MULTIMOORA. Renewable Energy, 162, 712-726. https://doi.org/10.1016/j.renene.2020.08.062
  • Ansari, Z. N., Kant, R., & Shankar, R. (2020). Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach. International Journal of Sustainable Engineering, 13(6), 473-494. https://doi.org/10.1080/19397038.2020.1758973
  • Başaran, B., & Çakir, S. (2021). Evaluation of food safety and halal criteria in supplier selection: an application in food sector with fuzzy COPRAS method. International Food Research Journal, 28(3), 576-585. ISSN: 19854668
  • Baykaşoğlu, A. (2010). Çok kriterli TIR çekici seçimi. LODER Lojistik Dergisi, 14, 32-36.
  • Baykasoğlu, A., & Golcuk, I. (2014). Çok kriterli tır çekici seçiminde bulanık integral yaklaşımı. 3. Ulusal Lojistik ve Tedarik Zinciri Kongresi, Karadeniz Teknik Üniversitesi, 15-17 Mayıs 2014, Trabzon, 776-786.
  • Baykaşoğlu, A., Dereli, T., Altun, K., (2011). Kullanılmış tır çekici seşimi: pratik bir karar destek yaklaşımı EVEN-SWAP. Lojistik, 19, 18-22
  • Baykaşoğlu, A., Kaplanoğlu, V., Durmuşoğlu, Z. D., & Şahin, C. (2013). Integrating fuzzy DEMATEL and fuzzy hierarchical TOPSIS methods for truck selection. Expert Systems with Applications, 40(3), 899-907. https://doi.org/10.1016/j.eswa.2012.05.046
  • Blagojević, A., Kasalica, S., Stević, Ž., Tričković, G., & Pavelkić, V. (2021). Evaluation of safety degree at railway crossings in order to achieve sustainable traffic management: A novel integrated fuzzy MCDM model. Sustainability, 13(2), 832. DOI: 10.3390/su13020832
  • Blagojević, A., Stević, Ž., Marinković, D., Kasalica, S., & Rajilić, S. (2020). A novel entropy-fuzzy PIPRECIA-DEA model for safety evaluation of railway traffic. Symmetry, 12(9), 1479. doi:10.3390/sym12091479
  • Chakraborty, S., & Prasad, K. (2016). A QFD-based expert system for industrial truck selection in manufacturing organizations. Journal of Manufacturing Technology Management.
  • Chan, F. T., Jha, A., & Tiwari, M. K. (2016). Bi-objective optimization of three echelon supply chain involving truck selection and loading using NSGA-II with heuristics algorithm. Applied soft computing, 38, 978-987.
  • Đalić, I., Stević, Ž., Karamasa, C., & Puška, A. (2020). A novel integrated fuzzy PIPRECIA–interval rough SAW model: Green supplier selection. Decision Making: Applications in Management and Engineering, 3(1), 126-145. DOI: https://doi.org/10.31181/dmame2003114d
  • de Sousa Junior, W. T., Souza, M. J. F., Cabral, I. E., & Diniz, M. E. (2014). Multi-Criteria Decision Aid methodology applied to highway truck selection at a mining company. Rem: Revista Escola de Minas, 67(3), 285-290.
  • Dhiman, H. S., & Deb, D. (2020). Fuzzy TOPSIS and fuzzy COPRAS based multi-criteria decision making for hybrid wind farms. Energy, 202, 117755. https://doi.org/10.1016/j.energy.2020.117755
  • Doğan, E. M., Eren, M., & Çelik, K. (2017). Lojistik sektöründe ağır ticari araç seçimi problemine yönelik COPRAS-G yöntemi ile karar verme. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 19(1), 153-178.
  • Garg, R., Kumar, R., & Garg, S. (2019). MADM-based parametric selection and ranking of E-learning websites using fuzzy COPRAS. IEEE Transactions on Education, 62(1), 11-18. DOI: 10.1109/TE.2018.2814611
  • Görçün, Ö. F. (2019). Uluslararası Taşımacılık İşletmelerinin Çekici Araç Seçimlerinin Entegre AHP, Entropi ve TOPSIS Yöntemleri Kullanılarak Analizi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 21(3), 899-922. https://doi.org/10.32709/akusosbil.521611
  • Hasheminezhad, A., Hadadi, F., & Shirmohammadi, H. (2021). Investigation and prioritization of risk factors in the collision of two passenger trains based on fuzzy COPRAS and fuzzy DEMATEL methods. Soft Computing, 25, 4677-4697. https://doi.org/10.1007/s00500-020-05478-3
  • Khorasani, S. T. (2018). Green supplier evaluation by using the integrated fuzzy AHP model and fuzzy copras. Process Integration and Optimization for Sustainability, 2(1), 17-25. DOI: 10.1007/s41660-017-0027-9
  • Marković, V., Stajić, L., Stević, Ž., Mitrović, G., Novarlić, B., & Radojičić, Z. (2020). A novel integrated subjective-objective mcdm model for alternative ranking in order to achieve business excellence and sustainability. Symmetry, 12(1), 164. DOI: 10.3390/SYM12010164
  • Nedeljković, M., Puška, A., Doljanica, S., Virijević Jovanović, S., Brzaković, P., Stević, Ž., & Marinkovic, D. (2021). Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA–Fuzzy MABAC model. Plos one, 16(2), e0246857. https://doi.org/10.1371/journal.pone.0246857
  • Puška, A., Nedeljković, M., Hashemkhani Zolfani, S., & Pamučar, D. (2021). Application of interval fuzzy logic in selecting a sustainable supplier on the example of agricultural production. Symmetry, 13(5), 774. DOI: 10.3390/sym13050774
  • Roozbahani, A., Ghased, H., & Shahedany, M. H. (2020). Inter-basin water transfer planning with grey COPRAS and fuzzy COPRAS techniques: A case study in Iranian Central Plateau. Science of the Total Environment, 726, 138499. https://doi.org/10.1016/j.scitotenv.2020.138499
  • Shaikh, A., Singh, A., Ghose, D., & Shabbiruddin. (2020). Analysis and selection of optimum material to improvise braking system in automobiles using integrated Fuzzy-COPRAS methodology. International Journal of Management Science and Engineering Management, 15(4), 265-273. https://doi.org/10.1080/17509653.2020.1772895
  • Stanković, M., Stević, Ž., Das, D. K., Subotić, M., & Pamučar, D. (2020). A new fuzzy MARCOS method for road traffic risk analysis. Mathematics, 8(3), 457. DOI: 10.3390/MATH8030457
  • Stevic, Ž., Stjepanovic, Ž., Božickovic, Z., Das, D. K., & Stanujkic, D. (2018). Assessment of Conditions for Implementing Information Technology in a Warehouse System: A Novel Fuzzy PIPRECIA Method. Symmetry, 10 (586), 1-28. doi: 10.3390/sym10110586.
  • Tolga, A. C., & Durak, G. (2019). Evaluating innovation projects in air cargo sector with fuzzy COPRAS. In International Conference on Intelligent and Fuzzy Systems (pp. 702-710). Springer, Cham. DOI: 10.1007/978-3-030-23756-1_84
  • Tomašević, M., Lapuh, L., Stević, Ž., Stanujkić, D., & Karabašević, D. (2020). Evaluation of criteria for the implementation of high-performance computing (HPC) in Danube Region countries using fuzzy PIPRECIA method. Sustainability, 12(7), 3017. https://doi.org/10.3390/su12073017
  • Vesković, S., Milinković, S., Abramović, B., & Ljubaj, I. (2020). Determining criteria significance in selecting reach stackers by applying the fuzzy PIPRECIA method. Operational Research in Engineering Sciences: Theory and Applications, 3(1), 72-88. DOI: https://doi.org/10.31181/oresta2001072v
  • Yazdani, Morteza., Alidoosti, Ali., Zavadskas, Edmundas, K. (2011). Risk Analysis of Critical Infrastructures Using Fuzzy Copras, Economic Research-Ekonomska Istraživanja, 24:4, 27-40, DOI: 10.1080/1331677X.2011.11517478.
  • Zarbakhshnia, N., Soleimani, H., & Ghaderi, H. (2018). Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed fuzzy COPRAS in the presence of risk criteria. Applied Soft Computing, 65, 307-319. DOI: 10.1016/j.asoc.2018.01.023
There are 31 citations in total.

Details

Primary Language English
Subjects Operation
Journal Section Articles
Authors

Aşkın Özdağoğlu 0000-0001-5299-0622

Gülin Zeynep Öztaş 0000-0002-6901-6559

Murat Kemal Keleş 0000-0003-0374-6839

Volkan Genç 0000-0003-2184-482X

Publication Date December 31, 2021
Submission Date October 7, 2021
Published in Issue Year 2021 Volume: 9 Issue: 2

Cite

APA Özdağoğlu, A., Öztaş, G. Z., Keleş, M. K., Genç, V. (2021). An Integrated PIPRECIA and COPRAS Method under Fuzzy Environment: A Case of Truck Tractor Selection. Alphanumeric Journal, 9(2), 269-298. https://doi.org/10.17093/alphanumeric.1005970

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