FUCOM-MOORA and FUCOM-MOOSRA: new MCDM-based knowledge-driven procedures for mineral potential mapping in greenfields

Abstract

In this study, we present the application of two novel hybrid multiple-criteria decision-making (MCDM) techniques in the mineral potential mapping (MPM), namely FUCOM-MOORA and FUCOM-MOOSRA, as robust computational frameworks for MPM. These were applied to a set of exploration targeting criteria of skarn. The multi-objective optimization method on the basis of ratio analysis (MOORA) and the multi-objective optimization on the basis of simple ratio analysis (MOOSRA) approaches are used to prioritize and rank individual cells. What makes MOORA and MOOSRA more reliable compared to many other methods is the fact that the optimizations procedure is applied to calculate the prospectivity score of individual unit cells. This reduces the uncertainty stemming from erroneous mathematical calculations. The full consistency method (FUCOM), on the other hand, is useful for assigning weights to the spatial proxies. The FUCOM method, as a pairwise comparison method, reduces a large number of pairwise comparisons of similar and popular approaches such as analytic hierarchy process (AHP) with $$n\left( {n - 1} \right)/2$$ n n - 1 / 2 and the best–worst method (BWM) with $$2n - 3$$ 2 n - 3 number of pairwise comparisons with $$n - 1$$ n - 1 which leads to a less time-consuming and more consistent performance compared with AHP and BWM. These were applied to a set of exploration targeting criteria of skarn iron deposits from Central Iran. Two potential maps were retrieved from the procedures applied, the comparison of which using correct classification rates and field checks revealed the superiority of FUCOM-MOOSRA over the FUCOM-MOORA.

D Numbers – Fucom – Fuzzy Rafsi Model for Selecting the Group of Construction Machines for Enabling Mobility

“…The FUCOM (Full Consistency Method) method is intended for determining the weight coefficients of the evaluation criteria. The method was first presented by Pamučar et al [36]; since then it has been applied in a large number of papers for solving various problems, such as: ▪ landfill site selection, together with the CODAS method [37], ▪ assessment of critical success factors for continuous academic quality assurance and accreditation, in the model with fuzzy AHP method [38], ▪ evaluation of the provisional sizing process in the clothing industry, with the fuzzy PIPRECIA method [39], ▪ selection of the best solution for business balance of the passenger railway operator, as a part of the validation test with the fuzzy AHP method [40], ▪ determination of macro location for railway network, in the model with the fuzzy TOPSIS method [41], ▪ selection of a distribution channel, in combination with the MARCOS method [42], ▪ solving the case study in the rubber glove industry, used in a hybrid model with the VIKOR method [43], ▪ for the purpose of assessing human resources, on which the overall efficiency of the enterprise depends, together with the MARCOS method [44], ▪ mineral potential mapping in greenfields, in the model with the MOORA and MOOSRA method [45], ▪ selection of vehicles with automatic guidance (AGVs), in combination with the R-ROV (Rough Range of Value) method [46], ▪ improvement of service quality measurement in the hybrid Delphi-FUCOM-SERVQUAL model [47], ▪ selection of a terrain vehicle for equipping military units, through the validation test of the AHP-DEA model, with the BWM method [48], ▪ selection of a sustainable supplier in a construction company, with the COPRAS method, while for the validation of the results the ARAS, WASPAS, SAW and MABAC methods were used in combination with rough numbers [49], ▪ evaluation of the sustainable performance of suppliers, with the MAIRCA method [50], ▪ selection of a location for a textile manufacturing facility, in combination with the GIS [51], and, ▪ selection of a fighter aircraft, with the ARAS method [52]. In addition to the classic FUCOM method, a fuzzified version of this method was used for solving practical problems, such as:…”

Determining the Riskiest Production Area Using Integrated Criteria Weights

“…Özdemir implemented MOORA and MOOSRA methods and the results were interpreted for smartphone selection [42] . Feizi et al advanced two novel hybrid MCDM techniques in the mineral potential mapping (MPM), called FUCOM-MOORA and FUCOM-MOOSRA, as robust computational frameworks for MPM to apply a set of exploration targeting criteria of skarn [43] . Narayanamoorthy et al carried out a new methodology based on Hesitant Fuzzy Subjective and Objective Weight Integrated Approach and Hesitant Fuzzy MOOSRA to find the most suitable bio-medical waste disposal methods [44] .…”

Sistem Pendukung Keputusan Penentuan Team Leader Menggunakan Metode MOOSRA

“…Penelitian terdahulu yang dilakukan oleh ahad safitra pada tahun 2021 terhdap pemilihan servicen advisor dari kandidat mekanik menggunakan sistem pendukung keputusan dan moosra dengan hasil penggunaan metode ini sangat sederhana dan selektif dalam membedakan terhadap keuntungan dan kerugian dan hasil akumulasi penelitian dari keseluruhan nilai terdapat nilai tertinggi dengan perbedaan nilai yang signifikansi tinggi [6]. Penelitian terdahulu lainnya yang dilakukan oleh faranak feizi dalam memilih mineral protein pada greenfield dimana pada penelitian ini digunakan kombinasi antara penggunaan fucom-moora dan fucom-moosra pada penelitian ini melihat kemungkinan dua diantara penyelesaikan kasus digunakan dengan tahapan yang sederhana dan memiliki nilai yang berbeda berdasrkan cost dan benefit tetapi tetap memiliki urutan yang sama" [7].…”