Document Type : Review Paper
Authors
1 Faculty of Mining, Petroleum & Geophysics Eng., Shahrood University of Technology, Shahrood, Iran
2 Department of Engineering and Safety, University of Tromsø, Tromsø, Norway, Tromsø, Norway
Abstract
The mining industry operates in a complex and dynamic environment and faces many challenges that can negatively affect sustainable development goals. To avoid these effects, mining needs to adopt strategic decisions. Therefore, it requires effective decision-making processes for resource optimization, operational efficiency, and sustainability. Multicriteria decision-making methods (MCDM) have been considered valuable decision-support tools in the mining industry. This article comprehensively examines MCDM methods and their applications in the mining industry. This article discusses the basic principles and concepts of MCDM methods, including the ability to prioritize and weigh conflicting, multiple criteria and support decision-makers in evaluating diverse options. According to the results, 1579 MCDM articles in mining have been published from the beginning to April 15, 2023, and a scientometric analysis was done on these articles. In another part of this article, 19 MCDM methods, among the most important MCDM methods in this field, have been examined. The process of doing work in 17 cases of the reviewed methods is presented visually. Overall, this paper is a valuable resource for researchers, mining industry professionals, policymakers, and decision-makers that can lead to a deeper understanding of the application of MCDM methods in mining. By facilitating informed decision-making processes, MCDM methods can potentially increase operational efficiency, resource optimization, and sustainable development in various mining sectors, ultimately contributing to mining projects' long-term success and sustainability.
Keywords
Main Subjects
[1]. Pouresmaieli, M., Ataei, M., Qarahasanlou, A. N., & Barabadi, A. (2023a). Building ecological literacy in mining communities: A sustainable development perspective. Case Studies in Chemical and Environmental Engineering, 100554.
[2]. Pouresmaieli, M., Ataei, M., Qarahasanlou, A. N., & Barabadi, A. (2023b). Integration of renewable energy and sustainable development with strategic planning in the mining industry. Results in Engineering, 20, 101412.
[3]. Azadeh, A., Osanloo, M., & Ataei, M. (2010). A new approach to mining method selection based on modifying the Nicholas technique. Applied Soft Computing, 10(4), 1040-1061.
[4]. Pouresmaieli, M., Ataei, M., Forouzandeh, P., Azizollahi, P., & Mahmoudifard, M. (2022). Recent Progress on Sustainable Phytoremediation of Heavy Metals from Soil. Journal of Environmental Chemical Engineering, 108482.
[5]. Pouresmaieli, M., Ataei, M., & Qarahasanlou, A. N. (2023). A scientometrics view on sustainable development in surface mining: Everything from the beginning. Resources policy, 82, 103410.
[6]. Pouresmaieli, M., Ataei, M., & Taran, A. (2022). Future mining based on internet of things (IoT) and sustainability challenges. International Journal of Sustainable Development & World Ecology, 1-18.
[7]. Ekrami, E., Pouresmaieli, M., sadat Hashemiyoon, E., Noorbakhsh, N., & Mahmoudifard, M. (2022). Nanotechnology: a sustainable solution for heavy metals remediation. Environmental Nanotechnology, Monitoring & Management, 100718.
[8]. Ekrami, E., Pouresmaieli, M., Shariati, P., & Mahmoudifard, M. (2021). A review on designing biosensors for the detection of trace metals. Applied Geochemistry, 104902.
[9]. Mardani, A., Zavadskas, E. K., Khalifah, Z., Zakuan, N., Jusoh, A., Nor, K. M., & Khoshnoudi, M. (2017). A review of multi-criteria decision-making applications to solve energy management problems: Two decades from 1995 to 2015. Renewable and Sustainable Energy Reviews, 71, 216-256.
[10]. Gupta, S. K., Khang, A., Somani, P., Dixit, C. K., & Pathak, A. (2023). Data Mining Processes and Decision-Making Models in the Personnel Management System. In Designing Workforce Management Systems for Industry 4.0 (pp. 85-104). CRC Press.
[11]. Mohammadi, S., Ataei, M., Kakaie, R., & Mirzaghorbanali, A. (2019). A New Roof Strata Cavability Index (RSCi) for longwall mining incorporating new rating system. Geotechnical and Geological Engineering, 37, 3619-3636.
[12]. Masir, R. N., Ataei, M., & Motahedi, A. (2021). Risk assessment of flyrock in surface mines using a FFTA-MCDM combination. Journal of Mining and Environment, 12(1), 191-203.
[13]. Mohammadi, S., Ataei, M., Khaloo Kakaie, R., & Mirzaghorbanali, A. (2018). Prediction of the main caving span in longwall mining using fuzzy MCDM technique and statistical method. Journal of Mining and Environment, 9(3), 717-726.
[14]. Pazand, K., Hezarkhani, A., & Ataei, M. (2012). Using TOPSIS approaches for predictive porphyry Cu potential mapping: A case study in Ahar-Arasbaran area (NW, Iran). Computers & Geosciences, 49, 62-71.
[15]. Rahimdel, M. J., & Ataei, M. (2014). Application of analytical hierarchy process to selection of primary crusher. International Journal of Mining Science and Technology, 24(4), 519-523.
[16]. Norouzi Masir, R., Ataei, M., & Mottahedi, A. (2021). Risk assessment of Flyrock in Surface Mines using a FFTA-MCDM Combination. Journal of Mining and Environment, 12(1), 191-203.
[17]. Pouresmaieli, M., & Osanloo, M. (2019a). Establishing a Model to Reduce the Risk of Premature Mine Closure. IOP Conference Series: Earth and Environmental Science,
[18]. Pouresmaieli, M., & Osanloo, M. (2019b). A Valuation Approach to Investigate the Sustainability of Sorkhe-Dizaj Iron Ore Mine of Iran. International Symposium on Mine Planning & Equipment Selection,
[19]. Ataei, M., Jamshidi, M., Sereshki, F., & Jalali, S. (2008). Mining method selection by AHP approach. Journal of the Southern African Institute of Mining and Metallurgy, 108(12), 741-749.
[20]. Ataei, M., Shahsavany, H., & Mikaeil, R. (2013). Monte Carlo Analytic Hierarchy Process (MAHP) approach to selection of optimum mining method. International Journal of Mining Science and Technology, 23(4), 573-578.
[21]. Bascetin, A. (2007). A decision support system using analytical hierarchy process (AHP) for the optimal environmental reclamation of an open-pit mine. Environmental Geology, 52, 663-672.
[22]. Chakraborty, S., Raut, R. D., Rofin, T., & Chakraborty, S. (2023). A comprehensive and systematic review of multi-criteria decision-making methods and applications in healthcare. Healthcare Analytics, 100232.
[23]. Azimi, R., Yazdani-Chamzini, A., Fouladgar, M. M., Zavadskas, E. K., & Basiri, M. H. (2011). Ranking the strategies of mining sector through ANP and TOPSIS in a SWOT framework. Journal of business economics and management, 12(4), 670-689.
[24]. Selvan, S. U., Saroglou, S. T., Joschinski, J., Calbi, M., Vogler, V., Barath, S., & Grobman, Y. J. (2023). Toward multi-species building envelopes: A critical literature review of multi-criteria decision-making for design support. Building and Environment, 110006.
[25]. Ataei, M., Divsalar, A., & Saberi, M. (2022). The bi-objective orienteering problem with hotel selection: An integrated text mining optimisation approach. Information Technology and Management, 1-29.
[26]. Bahrami, Y., Hassani, H., & Maghsoudi, A. (2022). Spatial modeling for mineral prospectivity using BWM and COPRAS as a new HMCDM method. Arabian Journal of Geosciences, 15(5), 394.
[27]. Pamučar, D., Ecer, F., Cirovic, G., & Arlasheedi, M. A. (2020). Application of improved best worst method (BWM) in real-world problems. Mathematics, 8(8), 1342.
[28]. Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57.
[29]. Bonab, S. R., Ghoushchi, S. J., Deveci, M., & Haseli, G. (2023). Logistic autonomous vehicles assessment using decision support model under spherical fuzzy set integrated Choquet Integral approach. Expert Systems with Applications, 214, 119205.
[30]. Bajpayee, T., Rehak, T., Mowrey, G., & Ingram, D. (2004). Blasting injuries in surface mining with emphasis on flyrock and blast area security. Journal of Safety Research, 35(1), 47-57.
[31]. Boateng‐Okrah, E., & Appiah Fening, F. (2012). TQM implementation: a case of a mining company in Ghana. Benchmarking: An International Journal, 19(6), 743-759.
[32]. Hosseinzadeh, A., Behzadian, K., Rossi, P., Karami, M., Ardeshir, A., & Torabi Haghighi, A. (2023). A new multi‐criteria framework to identify optimal detention ponds in urban drainage systems. Journal of Flood Risk Management, e12890.
[33]. Mena, R., Godoy, M., Catalán, C., Viveros, P., & Zio, E. (2023). Multi-objective two-stage stochastic unit commitment model for wind-integrated power systems: A compromise programming approach. International Journal of Electrical Power & Energy Systems, 152, 109214.
[34]. Baloyi, V. D., & Meyer, L. (2020). The development of a mining method selection model through a detailed assessment of multi-criteria decision methods. Results in Engineering, 8, 100172.
[35]. Kemmar, A., Ugarte, W., Loudni, S., Charnois, T., Lebbah, Y., Boizumault, P., & Cremilleux, B. (2014). Mining relevant sequence patterns with cp-based framework. 2014 IEEE 26th International Conference on Tools with Artificial Intelligence,
[36]. Emrouznejad, A., Amin, G. R., Ghiyasi, M., & Michali, M. (2023). A review of inverse data envelopment analysis: origins, development, and future directions. IMA journal of management mathematics, dpad006.
[37]. Kyrgiakos, L. S., Kleftodimos, G., Vlontzos, G., & Pardalos, P. M. (2023). A systematic literature review of data envelopment analysis implementation in agriculture under the prism of sustainability. Operational Research, 23(1), 7.
[38]. Zuo, Z., Guo, H., Li, Y., & Cheng, J. (2022). A two-stage DEA evaluation of Chinese mining industry technological innovation efficiency and eco-efficiency. Environmental Impact Assessment Review, 94, 106762.
[39]. Rabbani, M., Farrokhi-Asl, H., & Manavizadeh, N. (2017). Using Robust-DEA optimization approach to analyze performance and efficiency of a mine in north of Iran. Management Science Letters, 7(2), 97-110.
[40]. Bajec, P., Kontelj, M., & Groznik, A. (2020). Assessment of logistics platform efficiency using an integrated delphi analytic hierarchy process–data envelopment analysis approach: a novel methodological approach including a case study in Slovenia.
[41]. Taherdoost, H., & Madanchian, M. (2023). A Comprehensive Overview of the ELECTRE Method in Multi Criteria Decision-Making. Journal of Management Science & Engineering Research, 6(2).
[42]. Akbari, A., Zare, S., & Ataei, M. (2020). Ranking the Risk of Mechanized Tunnel construction in Large Cross Section by Fuzzy Multi Criteria Decision Making Methods in Western Alborz Tunnel. Journal of Mineral Resources Engineering, 5(2), 43-65.
[43]. Fahliani, Z. R., Ataei, M., Jalali, S. M. E., & Faraji, R. (2011). APPLICATION OF ELECTRE METHOD FOR SELECTION OF OPTUMUM SUPPORT SYSTEM FOR ACCESS TUNNEL IN GOOSHFILL MINE. International Multidisciplinary Scientific GeoConference: SGEM, 1, 693.
[44]. Agarwal, R., & Nishad, A. K. (2023). A Fuzzy Mathematical Modeling for Evaluation and Selection of a Best Sustainable and Resilient Supplier by Using EDAS Technique. Process Integration and Optimization for Sustainability, 1-10.
[45]. Torkayesh, A. E., Deveci, M., Karagoz, S., & Antucheviciene, J. (2023). A state-of-the-art survey of evaluation based on distance from average solution (EDAS): Developments and applications. Expert Systems with Applications, 119724.
[46]. Maksimović, M., Brzaković, M., Grahovac, M., & Jovanović, I. (2017). An approach for evaluation the safety and quality of transport at the open pit mines, based on the EDAS method. Mining and Metallurgy Engineering Bor(3-4), 139-144.
[47]. Ye, J., Du, S., & Yong, R. (2023). Mine safety evaluation method using correlation coefficients of consistency linguistic neutrosophic sets in a linguistic neutrosophic multivalued environment. Soft Computing, 1-11.
[48]. Darms, I. (2023). Fuzzy Analytic Hierarchy Process Utilization in Government Projects: A Systematic Review of Implementation Processes.
[49]. Tahernejad, M., Ataei, M., & Khalokakaie, R. (2012). Selection of the best strategy for Iran's quarries: SWOT-FAHP method. Journal of Mining and Environment, 3(1), 1-13.
[50]. Zarghami, M. (2011). Soft computing of the Borda count by fuzzy linguistic quantifiers. Applied Soft Computing, 11(1), 1067-1073.
[51]. Flegg, A. T., Lamonica, G. R., Chelli, F. M., Recchioni, M. C., & Tohmo, T. (2021). A new approach to modelling the input–output structure of regional economies using non-survey methods. Journal of Economic Structures, 10(1), 1-31.
[52]. Flegg, A. T., & Tohmo, T. (2018). The Regionalization of national input–output tables: a review of the performance of two key non-survey methods. Applications of the input-output framework, 347-386.
[53]. Chakraborty, S., Datta, H. N., & Chakraborty, S. (2023). Grey Relational Analysis-Based Optimization of Machining Processes: a Comprehensive Review. Process Integration and Optimization for Sustainability, 1-31.
[54]. Kuo, T. (2017). A review of some modified grey relational analysis models. The Journal of grey system, 29(3), 70-78.
[55]. Abdelrasoul, M. E., Wang, G., Kim, J.-G., Ren, G., Abd-El-Hakeem Mohamed, M., Ali, M. A., & Abdellah, W. R. (2022). Review on the Development of Mining Method Selection to Identify New Techniques Using a Cascade-Forward Backpropagation Neural Network. Advances in Civil Engineering, 2022.
[56]. Janovac, T., Karabašević, D., Maksimović, M., & Radanov, P. (2018). Selection of the motivation strategy for employees in the mining industry using the GRA method. Mining and Metallurgy Engineering Bor(1-2), 157-164.
[57]. Jung, Y., Do, T., Choi, U. S., Jung, K.-W., & Choi, J.-W. (2022). Cage-like amine-rich polymeric capsule with internal 3D center-radial channels for efficient and selective gold recovery. Chemical Engineering Journal, 438, 135618.
[58]. Suwitno, S., Chandra, N. D., & Daniawan, B. (2023). Boarding House Provider Information with Multi Attribute Utility Theory (MAUT) Method. bit-Tech, 5(3), 155-165.
[59]. Von Winterfeldt, D., & Fischer, G. W. (1975). Multi-attribute utility theory: models and assessment procedures. Utility, Probability, and Human Decision Making: Selected Proceedings of an Interdisciplinary Research Conference, Rome, 3–6 September, 1973,
[60]. Kamenopoulos, S., Agioutantis, Z., & Komnitsas, K. (2018). A new hybrid decision support tool for evaluating the sustainability of mining projects. International Journal of Mining Science and Technology, 28(2), 259-265.
[61]. Saki, F., Dehghani, H., Jodeiri Shokri, B., & Bogdanovic, D. (2020). Determination of the most appropriate tools of multi-criteria decision analysis for underground mining method selection—a case study. Arabian Journal of Geosciences, 13(23), 1271.
[62]. Stipanovic, I., Bukhsh, Z. A., Reale, C., & Gavin, K. (2021). A multiobjective decision-making model for risk-based maintenance scheduling of railway earthworks. Applied Sciences, 11(3), 965.
[63]. Diaby, V., Campbell, K., & Goeree, R. (2013). Multi-criteria decision analysis (MCDA) in health care: a bibliometric analysis. Operations Research for Health Care, 2(1-2), 20-24.
[64]. Huang, I. B., Keisler, J., & Linkov, I. (2011). Multi-criteria decision analysis in environmental sciences: Ten years of applications and trends. Science of the total environment, 409(19), 3578-3594.
[65]. Riz, G., Santos, E. A. P., & de Freitas Rocha Loures, E. (2017). Interoperability assessment in health systems based on process mining and MCDA methods. Recent Advances in Information Systems and Technologies: Volume 1 5,
[66]. Stevanović, D., Lekić, M., Kržanović, D., & Ristović, I. (2018). Application of MCDA in selection of different mining methods and solutions. Advances in Science and Technology. Research Journal, 12(1).
[67]. Takam Tiamgne, X., Kanungwe Kalaba, F., Raphael Nyirenda, V., & Phiri, D. (2022). Modelling areas for sustainable forest management in a mining and human dominated landscape: A Geographical Information System (GIS)-Multi-Criteria Decision Analysis (MCDA) approach. Annals of GIS, 28(3), 343-357.
[68]. Behzadian, M., Kazemzadeh, R. B., Albadvi, A., & Aghdasi, M. (2010). PROMETHEE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 200(1), 198-215.
[69]. Yu, D., Liu, Y., & Xu, Z. (2023). Analysis of knowledge evolution in PROMETHEE: A longitudinal and dynamic perspective. Information Sciences, 642, 119151.
[70]. Balusa, B. C., & Singam, J. (2018). Underground mining method selection using WPM and PROMETHEE. Journal of The Institution of Engineers (India): Series D, 99, 165-171.
[71]. Namin, F. S., Ghadi, A., & Saki, F. (2022). A literature review of Multi Criteria Decision-Making (MCDM) towards mining method selection (MMS). Resources policy, 77, 102676.
[72]. Ebrahimabadi, A., Pouresmaieli, M., Afradi, A., Pouresmaeili, E., & Nouri, S. (2018). Comparing two methods of PROMETHEE and Fuzzy TOPSIS in selecting the best plant species for the reclamation of Sarcheshmeh copper mine. Asian Journal of Water, Environment and Pollution, 15(2), 141-152.
[73]. Mikaeil, R., ABDOLLAHI, K. M., Sadegheslam, G., & Ataei, M. (2015). Ranking sawability of dimension stone using PROMETHEE method.
[74]. Mikaeil, R., Esmaeilzadeh, A., Shaffiee Haghshenas, S., Ataei, M., Hajizadehigdir, S., Jafarpour, A., Kim, T.-H., & Geem, Z. W. (2022). Evaluation of dimension stone according to resistance to freeze–thaw cycling to use in cold regions. Journal of Soft Computing in Civil Engineering, 6(1), 88-109.
[75]. Behzadian, M., Otaghsara, S. K., Yazdani, M., & Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with Applications, 39(17), 13051-13069.
[76]. Li, K., Chen, C.-Y., & Zhang, Z.-L. (2023). Mining online reviews for ranking products: A novel method based on multiple classifiers and interval-valued intuitionistic fuzzy TOPSIS. Applied Soft Computing, 139, 110237.
[77]. Ataei, M., Sereshki, F., Jamshidi, M., & Jalali, S. (2008). Suitable mining method for Golbini No. 8 deposit in Jajarm (Iran) using TOPSIS method. Mining Technology, 117(1), 1-5.
[78]. Mikaeil, R., Ataei, M., & Yousefi, R. (2011). Evaluating the power consumption in carbonate rock sawing porocess by using FDAHP and TOPSIS techniques. Efficient Decision Support Systems—Practice and Challenges in Multidisciplinary Domains, 413-436.
[79]. Safari, M., Kakaei, R., Ataei, M., & Karamoozian, M. (2012). Using fuzzy TOPSIS method for mineral processing plant site selection. Arabian Journal of Geosciences, 5(5), 1011-1019.
[80]. Gul, M., Celik, E., Aydin, N., Gumus, A. T., & Guneri, A. F. (2016). A state of the art literature review of VIKOR and its fuzzy extensions on applications. Applied Soft Computing, 46, 60-89.
[81]. Mardani, A., Zavadskas, E. K., Govindan, K., Amat Senin, A., & Jusoh, A. (2016). VIKOR technique: A systematic review of the state of the art literature on methodologies and applications. Sustainability, 8(1), 37.
[82]. Hayati, M., Rajabzadeh, R., & Darabi, M. (2015). Determination of optimal block size in Angouran mine using VIKOR method. Journal of Materials and Environmental Science, 6(11), 3236-3244.
[83]. Mijalkovski, S., Despodov, Z., Mirakovski, D., Adjiski, V., Doneva, N., & Mijalkovska, D. (2021). Mining method selection for underground mining with the application of VIKOR method. Podzemni radovi(39), 11-22.
[84]. Tabasi, S., & Kakha, G. (2021). An application of fuzzy-VIKOR method in environmental impact assessment of the boog mine Southeast of Iran. International Journal of Engineering, 34(6), 1545-1556.
[85]. Chakraborty, S., Datta, H. N., Kalita, K., & Chakraborty, S. (2023). A narrative review of multi-objective optimization on the basis of ratio analysis (MOORA) method in decision making. OPSEARCH, 1-44.
[86]. Ajrina, A. S., Sarno, R., Ginardi, H., & Fajar, A. (2020). Mining zone determination of natural sandy gravel using fuzzy AHP and SAW, MOORA, and COPRAS methods. Int. J. Intell. Eng. Syst, 13(5), 560-571.
[87]. Setyono, R. P., & Sarno, R. (2019). Comparative method of Moora and CoprAs based on weighting of the best worst method in supplier selection at ABC mining companies in Indonesia. 2019 International Conference on Information and Communications Technology (ICOIACT),
[88]. Stefano, N. M., Casarotto Filho, N., Vergara, L. G. L., & da Rocha, R. U. G. (2015). COPRAS (Complex Proportional Assessment): state of the art research and its applications. IEEE Latin America Transactions, 13(12), 3899-3906.
[89]. Fan, J., Cheng, R., & Wu, M. (2022). R-Set COPRAS (R-COPRAS) Methods-Based Multi-Attribute Decision-Making With RBM and RGBM Operators: A Case Study of Smart Mine Project Safety Assessment. IEEE Access, 10, 43481-43500.
[90]. Fouladgar, M. M., Yazdani-Chamzini, A., Lashgari, A., Zavadskas, E. K., & Turskis, Z. (2012). Maintenance strategy selection using AHP and COPRAS under fuzzy environment. International journal of strategic property management, 16(1), 85-104.
[91]. Si, S.-L., You, X.-Y., Liu, H.-C., & Zhang, P. (2018). DEMATEL technique: A systematic review of the state-of-the-art literature on methodologies and applications. Mathematical Problems in Engineering, 2018, 1-33.
[92]. Ataei, M., & Norouzi Masir, R. (2020). A fuzzy DEMATEL based sustainable development index (FDSDI) in open pit mining–a case study. Rudarsko-geološko-naftni zbornik, 35(1), 1-11.
[93]. Babaeian, M., Ataei, M., Sereshki, F., Sotoudeh, F., & Mohammadi, S. (2019). A new framework for evaluation of rock fragmentation in open pit mines. Journal of Rock Mechanics and Geotechnical Engineering, 11(2), 325-336.
[94]. Mohammadfam, I., Khajevandi, A. A., Dehghani, H., Babamiri, M., & Farhadian, M. (2022). Analysis of factors affecting human reliability in the mining process design using Fuzzy Delphi and DEMATEL methods. Sustainability, 14(13), 8168.
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