An interval-valued fuzzy MULTIMOOSRAL method for supplier evaluation in oil production projects

Document Type : Research Paper

Authors

Department of Industrial Engineering, Shahed University, Tehran, Iran

10.22070/jqepo.2024.19451.1282

Abstract

Meticulous project planning is pivotal for ensuring successful project outcomes, with strategic decision-making being a core component of this process. Among these decisions, selecting the right contractor is of paramount importance, particularly in the oil and gas sector where complexity, stringent safety regulations, and significant financial stakes are prevalent. The choice of contractor can significantly affect the project's success, highlighting the need for a meticulous selection process. This study presents a new approach for supplier selection in the oil and gas industry, utilizing an Interval-Valued Fuzzy MULTIMOOSRAL (IVF-MULTIMOOSRAL) method. This advanced methodology synthesizes the strengths of MOOSRA, MOORA, and MULTIMOORA techniques with interval-valued fuzzy sets to manage uncertainties in decision-making. Through a case study involving the evaluation of ten potential suppliers for a Vietnamese petroleum company, the IVF-MULTIMOOSRAL method demonstrates its practical application. The study assesses suppliers based on fifteen sub-criteria within five main categories: reliability, capability, agility, effective asset management, and cost. By providing a comprehensive framework for evaluating suppliers amidst uncertainty, this method facilitates more informed and adequate decision-making in the oil and gas supply chain. The IVF-MULTIMOOSRAL approach distinguishes itself by evaluating and ranking options across multiple criteria, ultimately integrating these assessments into a unified rating. This multifaceted approach not only enhances the precision of the selection process but also underscores the critical nature of the factors being evaluated.

Keywords

References

Akkaya, G., Turanoğlu, B., & Öztaş, S. (2015). An integrated fuzzy AHP and fuzzy MOORA approach to the problem of industrial engineering sector choosing. Expert Systems with Applications, 42(24), 9565–9573. https://doi.org/10.1016/j.eswa.2015.07.061
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
Ashtiani, B.; Haghighirad, F. Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets. Applied Soft Computing. 2009, 9(2), 457-461. 
Attri, R., & Grover, S. (2014). Decision making over the production system life cycle: MOORA method. International Journal of System Assurance Engineering and Management, 5(3), 320–328. https://doi.org/10.1007/s13198-013-0169-2
Aytaç Adalı, E., & Tuş Işık, A. (2017). The multi-objective decision making methods based on MULTIMOORA and MOOSRA for the laptop selection problem. Journal of Industrial Engineering International, 13(2), 229–237. https://doi.org/10.1007/s40092-016-0175-5
Bai, W., Zhang, C., Zhai, Y., Sangaiah, A. K., Wang, B., & Li, W. Cognitive Analysis of Medical Decision-Making: An Extended MULTIMOORA-Based Multigranulation Probabilistic Model with Evidential Reasoning. Cognitive Computation. 2024, 1-19.
Baležentis, A., Baležentis, T., & Brauers, W. K. M. (2012). Personnel selection based on computing with words and fuzzy MULTIMOORA. Expert Systems with Applications, 39(9), 7961–7967. https://doi.org/10.1016/j.eswa.2012.01.100
Behzadipour, A., Gitinavard, H., & Akbarpour Shirazi, M. (2022). A novel hierarchical dynamic group decision-based fuzzy ranking approach to evaluate the green road construction suppliers. Scientia Iranica.
Biswas, S., Pamučar, D., Božanić, D., & Halder, B. (2022). A new spherical fuzzy LBWA-MULTIMOOSRAL framework: Application in evaluation of leanness of MSMEs in India. Mathematical Problems in Engineering, 2022, 1–17. https://doi.org/10.1155/2022/5480848
Brauers, W. K. M. (2004). Optimization Methods for a Stakeholder Society. A Revolution in Economic Thinking by Multiobjective Optimization. Kluwer.
Brauers, W. K. M., & Zavadskas, E. K. (2010). PROJECT MANAGEMENT BY MULTIMOORA AS AN INSTRUMENT FOR TRANSITION ECONOMIES / PROJEKTŲ VADYBA SU MULTIMOORA KAIP PRIEMONĖ PEREINAMOJO LAIKOTARPIO ŪKIAMS. Technological and Economic Development of Economy, 16(1), 5–24. https://doi.org/10.3846/tede.2010.01
Brauers, W. K. M., & Zavadskas, E. K. (2011). Multimoora optimization used to decide on a bank loan to buy property. Technological and Economic Development of Economy, 17(1), 174–188. https://doi.org/10.3846/13928619.2011.560632
Chen, S. Fuzzy system reliability analysis based on vague set theory. Proceedings of the IEEE International Conference on Systems. Man, 1997. 2, 12-15.
Chen, S.J.; Chen, S.M. Fuzzy risk analysis based on measures of similarity between interval-valued fuzzy numbers. Computers & Mathematics with Applications. 2008, 55(8), 1670-1685. 
Dorfeshan, Y., Jolai, F., & Mousavi, S. M. (2023). A multi-criteria decision-making model for analyzing a project-driven supply chain under interval type-2 fuzzy sets. Applied Soft Computing, 148, 110902.
Emovon, I., Okpako, O. S., & Edjokpa, E. (2021). Application of fuzzy MOORA method in the design and fabrication of an automated hammering machine. World Journal of Engineering, 18(1), 37–49. https://doi.org/10.1108/wje-07-2020-0250
Gidiagba, J., Tartibu, L., & Okwu, M. (2023). Sustainable supplier selection in the oil and gas industry: An integrated multi-criteria decision-making approach. Procedia Computer Science, 217, 1243–1255. https://doi.org/10.1016/j.procs.2022.12.323
Global crude oil demand 2024. (n.d.). Statista. Retrieved August 2, 2024, from https://www.statista.com/statistics/271823/global-crude-oil-demand/
Gorzałczany, M.B. A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets and Systems. 1987, 21(1), 1-17.
Grattan-Guinness, I. Fuzzy Membership Mapped onto Intervals and Many-Valued Quantities. Math. Log. Q. 1976, 22, 149-160.
Hong, D.H.; Lee S. Some algebraic properties and a distance measure for interval-valued fuzzy numbers. Information Sciences. 2002, 148(1), 1-10.
Jahangirzadeh, A., Mousavi, S. M., & Dorfeshan, Y. (2020). An extended grey relational analysis based on COPRAS method for sustainable supplier selection in project procurement problems. Journal of Quality Engineering and Production Optimization, 5(1), 103-118.
Karande, P., & Chakraborty, S. (2012). Application of multi-objective optimization on the basis of ratio analysis (MOORA) method for materials selection. Materials in Engineering, 37, 317–324. https://doi.org/10.1016/j.matdes.2012.01.013
Karnik, N.N.; J.M. Mendel, Operations on type-2 fuzzy sets. Fuzzy Sets and Systems. 2001, 122(2), 327-348. 
Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Lithuanian Academy of Sciences. Informatica (Vilnius), 26(3), 435–451. https://doi.org/10.15388/informatica.2015.57
Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2018). Simultaneous evaluation of criteria and alternatives (SECA) for multi-criteria decision-making. Lithuanian Academy of Sciences. Informatica (Vilnius), 29(2), 265–280. https://doi.org/10.15388/informatica.2018.167
Khorshidi, M., Erkayman, B., Albayrak, Ö., Kılıç, R., & Demir, H. İ. (2022). Solar power plant location selection using integrated fuzzy DEMATEL and fuzzy MOORA method. International Journal of Ambient Energy, 43(1), 7400–7409. https://doi.org/10.1080/01430750.2022.2068067
Liu, P., Gao, H., & Fujita, H. (2021). The new extension of the MULTIMOORA method for sustainable supplier selection with intuitionistic linguistic rough numbers. Applied Soft Computing, 99(106893), 106893. https://doi.org/10.1016/j.asoc.2020.106893
Machesa, M., Tartibu, L., & Okwu, M. (2020). Selection of sustainable supplier(s) in a paint manufacturing company using hybrid meta-heuristic algorithm. The South African Journal of Industrial Engineering, 31(3). https://doi.org/10.7166/31-3-2429
Mahmoudian Azar Sharabiani, A., & Mousavi, S. M. (2023). A Web-Based Decision Support System for Project Evaluation with Sustainable Development Considerations Based on Two Developed Pythagorean Fuzzy Decision Methods. Sustainability, 15(23), 16477.
Mousavi, S. M., Vahdani, B., Gitinavard, H., & Hashemi, H. (2016). Solving robot selection problem by a new interval-valued hesitant fuzzy multi-attributes group decision method. International Journal of Industrial Mathematics, 8(3), 231-240.
Nasri, S. A., Ehsani, B., Hosseininezhad, S. J., & Safaie, N. (2023). A sustainable supplier selection method using integrated Fuzzy DEMATEL–ANP–DEA approach (case study: Petroleum Industry). Environment Development and Sustainability, 25(11), 12791–12827. https://doi.org/10.1007/s10668-022-02590-2
Ozcelik, G., Aydoğan, E. K., & Gencer, C. (2014). A hybrid moora-fuzzy algorithm for special education and rehabilitation center selection. Journal of Military and Information Science, 2(3), 53. https://doi.org/10.17858/jmisci.53708
Pamučar, D., & Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications, 42(6), 3016–3028. https://doi.org/10.1016/j.eswa.2014.11.057
Pamučar, D., Stević, Ž., & Sremac, S. (2018). A new model for determining weight coefficients of criteria in MCDM models: Full Consistency Method (FUCOM). Symmetry, 10(9), 393. https://doi.org/10.3390/sym10090393
Patnaik, P. K., Swain, P. T. R., Mishra, S. K., Purohit, A., & Biswas, S. (2020). Composite material selection for structural applications based on AHP-MOORA approach. Materials Today: Proceedings, 33, 5659–5663. https://doi.org/10.1016/j.matpr.2020.04.063 
Rani, P., Mishra, A. R., Krishankumar, R., Ravichandran, K. S., & Kar, S. (2021). Multi-criteria food waste treatment method selection using single-valued neutrosophic-CRITIC-MULTIMOORA framework. Applied Soft Computing, 111(107657), 107657. https://doi.org/10.1016/j.asoc.2021.107657
Rong, Y., Yu, L., Liu, Y., Peng, X., & Garg, H. (2024). An integrated group decision-making framework for assessing S3PRLPs based on MULTIMOORA-WASPAS with q-rung orthopair fuzzy information. Artificial Intelligence Review, 57(6). https://doi.org/10.1007/s10462-024-10782-7
Rong, Y., Yu, L., Liu, Y., Peng, X., & Garg, H. An integrated group decision-making framework for assessing S3PRLPs based on MULTIMOORA-WASPAS with q-rung orthopair fuzzy information. Artificial Intelligence Review. 2024, 57(6), 163.
Salimian, S., & Mousavi, S. M. (2023). A multi-criteria decision-making model with interval-valued intuitionistic fuzzy sets for evaluating digital technology strategies in COVID-19 pandemic under uncertainty. Arabian Journal for Science and Engineering, 48(5), 7005-7017.
Salimian, S., Mousavi, S. M., Tupenaite, L., & Antucheviciene, J. (2023). An integrated multi-criteria decision model to select sustainable construction projects under intuitionistic fuzzy conditions. Buildings, 13(4), 848.
Sarkis, J., & Talluri, S. (2002). A model for strategic supplier selection. Journal of Supply Chain Management, 38(4), 18–28. https://doi.org/10.1111/j.1745-493x.2002.tb00117.x
Shang, Z., Yang, X., Barnes, D., & Wu, C. (2022). Supplier selection in sustainable supply chains: Using the integrated BWM, fuzzy Shannon entropy, and fuzzy MULTIMOORA methods. Expert Systems with Applications, 195(116567), 116567. https://doi.org/10.1016/j.eswa.2022.116567
Shayani Mehr, P., Hafezalkotob, A., Fardi, K., Seiti, H., Movahedi Sobhani, F., & Hafezalkotob, A. (2022). A comprehensive framework for solar panel technology selection: A BWM‐ MULTIMOOSRAL approach. Energy Science & Engineering, 10(12), 4595–4625. https://doi.org/10.1002/ese3.1292
Siddiqui, Z. A., & Tyagi, K. (2016). Application of fuzzy-MOORA method: Ranking of components for reliability estimation of component-based software systems. Decision Science Letters, 169–188. https://doi.org/10.5267/j.dsl.2015.6.005
Stanujkić, D., Zavadskas, E. K., Karabašević, D., Smarandache, F., & Turskis, Z. (2017). The use of Pivot Pairwise Relative Criteria Importance Assessment Method for determining weights of criteria. Romanian Journal of Economic Forecasting, 20(4), 116–133.
Stanujkic, D., Zavadskas, E. K., Karabasevic, D., Turskis, Z., & Keršulienė, V. (2017). New group decision-making Arcas approach based on the integration of the Swara and the Aras methods adapted for negotiations. Journal of Business Economics and Management, 18(4), 599–618. https://doi.org/10.3846/16111699.2017.1327455
Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & Industrial Engineering, 140(106231), 106231. https://doi.org/10.1016/j.cie.2019.106231
Ulutaş, A., Popovic, G., Stanujkic, D., Karabasevic, D., Zavadskas, E. K., & Turskis, Z. (2020). A new hybrid MCDM model for personnel selection based on a novel grey PIPRECIA and grey OCRA methods. Mathematics, 8(10), 1698. https://doi.org/10.3390/math8101698
Ulutaş, A., Stanujkic, D., Karabasevic, D., Popovic, G., Zavadskas, E. K., Smarandache, F., & Brauers, W. K. M. (2021). Developing of a novel integrated MCDM MULTIMOOSRAL approach for supplier selection. Lithuanian Academy of Sciences. Informatica (Vilnius), 145–161. https://doi.org/10.15388/21-infor445
Vahdani, B.; Hadipour, H. Extension of VIKOR method based on interval-valued fuzzy sets. The International Journal of Advanced Manufacturing Technology. 2010, 47(9), 1231-1239. 
Vahdani, B.; Hadipour, H. Extension of VIKOR method based on interval-valued fuzzy sets. The International Journal of Advanced Manufacturing Technology. 2010, 47(9), 1231-1239.
Wang, C.-N., Huang, Y.-F., Cheng, I.-F., & Nguyen, V. T. (2018). A Multi-Criteria Decision-Making (MCDM) approach using hybrid SCOR metrics, AHP, and TOPSIS for supplier evaluation and selection in the gas and oil industry. Processes (Basel, Switzerland), 6(12), 252. https://doi.org/10.3390/pr6120252
Wang, C.-N., Tsai, H.-T., Ho, T.-P., Nguyen, V.-T., & Huang, Y.-F. (2020). Multi-Criteria Decision Making (MCDM) model for supplier evaluation and selection for oil production projects in Vietnam. Processes (Basel, Switzerland), 8(2), 134. https://doi.org/10.3390/pr8020134
Wang, P., Fu, Y., Liu, P., Zhu, B., Wang, F., & Pamucar, D. Evaluation of ecological governance in the Yellow River basin based on Uninorm combination weight and MULTIMOORA-Borda method. Expert Systems with Applications. 2024, 235, 121227.
Wood, D. A. (2016). Supplier selection for development of petroleum industry facilities, applying multi-criteria decision-making techniques including fuzzy and intuitionistic fuzzy TOPSIS with flexible entropy weighting. Journal of Natural Gas Science and Engineering, 28, 594–612. https://doi.org/10.1016/j.jngse.2015.12.021
Yang, Y., & Zhang, C. (2023). MULTIMOORA method-based Schweizer–Sklar operations for CO2 geological storage site selection under Pythagorean fuzzy environment. International Journal of Computational Intelligence Systems, 16(1). https://doi.org/10.1007/s44196-023-00201-0
Yao, J.S.; Lin, F.T. Constructing a fuzzy flow-shop sequencing model based on statistical data. International Journal of Approximate Reasoning. 2002, 29(3), 215-234. 
Yazdani, M., Zarate, P., Kazimieras Zavadskas, E., & Turskis, Z. (2019). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57(9), 2501–2519. https://doi.org/10.1108/md-05-2017-0458
Zadeh, L.A. The concept of a linguistic variable and its application to approximate reasoning—I. Information sciences, 1975, 8, 327-348. 
Zavadskas, E. K., Bausys, R., Lescauskiene, I., & Usovaite, A. (2021). MULTIMOORA under interval-valued neutrosophic sets as the basis for the quantitative heuristic evaluation methodology HEBIN. Mathematics, 9(1), 66. https://doi.org/10.3390/math9010066
Zhou, Q., Ye, C., & Geng, X. A decision framework of offshore wind power station site selection using a MULTIMOORA method under Pythagorean hesitant fuzzy environment. Ocean Engineering. 2024, 291, 116416.
Zimmermann, H.-J. Fuzzy set theory and mathematical programming. Fuzzy sets theory and applications. 1986, 99-114.
Journal of Quality Engineering and Production Optimization
Volume 8, Issue 1
May 2023
Pages 217-241

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