Combining the Experimental Techniques of Mining Method Selection with Fuzzy Decision Making (Case Study: Mehdi Abad Lead & Zinc Mine)

Document Type : Research Article



2 Mine Optimization Lab- faculty of engineering- Imam Khomeini international university

3 zanjan university

4 Kavoshgaran


Mining method selection (MMS) is one of the most important decisions in conceptual and feasibility study of mine designs to selecting the least costly method of exploitation of ore which is in accordance with the reserve characteristics such as geological, geometric, and geomechanical, that safety, technical and economic constraints are taken into account. MMS techniques can be classified into three categories: qualitative techniques, empirical models, and decision making. To reduce the weaknesses of the empirical models, in this study, by combining it with the Fuzzy analytical hierarchy process (FAHP) and Fuzzy PROMETEE decision-making technique, a suitable mining method in Mehdi Abad lead & zinc reserve has been proposed. First, using the experimental patterns: Nicholas, Nicholas modified, UBC, and UBC modified, the most suitable methods were identified. These methods include: Open-pit, sublevel stopping, room and pillar, and cut and fill that obtained the highest scores. For the implementation of Fuzzy MADM methods, the technical, economic, and environmental factors affecting the selection of the extraction method were determined based on the experts' opinions and their weights were calculated with the FAHP group technique. In the last step, by applying the Fuzzy PROMETEE technique, prioritization of the mining method was performed. Accordingly, open-pit mining was selected as the most suitable alternative. The proposed model has advantages in comparison with previous mining method selection techniques including weighting criteria with group decision making by FAHP, apply of Fuzzy data according to a real condition, having a strong theoretic structure based on Fuzzy PROMETEE.  


Main Subjects

[1] Dehghani, H., A. Siami, and P. Haghi, A new model for mining method selection based on grey and TODIM methods. Journal of Mining and Environment, 2017. 8(1): p. 49-60.
[2] S Shariati, S., A. Yazdani-Chamzini, and B. Pourghaffari Bashari, Mining method selection by using an integrated model. International Research Journal of Applied and Basic Sciences, 2013. 6(2): p. 199-214.
[3] F.Samimi Namin, K Shahriar, A.Bascetin, and S.H.Ghodsypour, Practical applications from decision-making techniques for selection of suitable mining method in Iran. Gospodarka Surowcami Mineralnymi, 2009. 25: p. 57-77.
[4] J.P Brans. Lingenierie de la decision, Elaboration dinstruments daide a la decision. Methode PROMETHEE. In: Nadeau, R., Landry, M. (Eds.), Laide a la Decision: Nature, Instrument s et Perspectives Davenir. Presses de Universite Laval, Qu ebec, Canada, 1982, pp. 183–213.
[5] J.P.Brans, P.Vincke, B, Mareschal, How to select and how to rank projects: The Promethee method. European J. Oper. Res. 1986, 24, 228-238.
[6] J.P Brans, B.Mareschal, PROMCALC and GAIA: A new decision support system for multicriteria decision aid. Decision Support Systems, 1994, 12, 297-310.
[7] M. Gul, E. Celik, A.T. Gumus, A.F. Guneri, A fuzzy logic based PROMETHEE method for material selection problems, Beni-Suef University Journal of Basic and Applied Sciences, 7(1) (2018) 68-79.
[8] D. Bogdanovic, D. Nikolic, I. Ilic, Mining method selection by integrated AHP and PROMETHEE method, Anais da Academia Brasileira de Ciências, 84(1) (2012) 219-233.
[9] A. De Almeida, L. Alencar, C. De Miranda, Mining methods selection based on multicriteria models, in, Taylor and Francis Group, London, 2005, pp. 19-24.
[10] C. Kahraman, Fuzzy multi-criteria decision making: theory and applications with recent developments, Springer Science & Business Media, 2008.
[11] A.Shahmardan, and M.H. Zadeh, An integrated approach for solving a MCDM problem, Combination of Entropy Fuzzy and F-PROMETHEE techniques. Journal of Industrial Engineering and Management (JIEM), 2013. 6(4): p. 1124-1138.
[12] Y.-H. Chen, T.-C. Wang, C.-Y. Wu, Strategic decisions using the fuzzy PROMETHEE for IS outsourcing, Expert Systems with Applications, 38(10) (2011) 13216-13222.
[13] S.M.H. Motlagh, M. Behzadian, J. Ignatius, M. Goh, M.M. Sepehri, T.K. Hua, Fuzzy PROMETHEE GDSS for technical requirements ranking in HOQ, The International Journal of Advanced Manufacturing Technology, 76(9) (2015) 1993-2002.
[14] Klir, G. J., Yuan, B., Fuzzy sets and fuzzy logic, Theory and applications, Prentice Hall PTR Publisher, 1995, 97-99
[15] J.Geldermann, T., Spengler, Rentz, O., Fuzzy outranking for environmental assessment. Case study: iron and steel making industry. Fuzzy Sets Syst, 115 (1), 45–65.
[16] G. Popović, B. Đorđević, D. Milanović, Multiple criteria approach in the mining method selection, Industrija, 47(4) (2019) 47-62.
[17] J., Aczel, T. L Saaty, Proceduar for synthesizing ratio judgments, Journal of mathematical pcychology, 1983, 27, 93-102.
[18] D.Nicholas, , J.Mark, "Feasibility study–selection of a mining method integrating rock mechanics and mine planning, 5th Rapid Excavation and Tunneling Conference, San Francisco, 1981, Vol.2, P:1018-1031,
[19] C.Clayton, , R.Pakalnis,  J.Meech, , "A knowledge-based system for selecting a mining method", International conference on Intelligent Processing and Manufacturing of Materials (IPPM), 2002, Canada
[20] O. Senvar., G. Tuzkaya, and C. Kahraman, Multi criteria supplier selection using fuzzy PROMETHEE method, in Supply chain management under fuzziness 2014, Springer. p. 21-34.