Multi-Criteria Decision Making in Mining Method Selection

Selecting an appropriate mining method involves the systematic evaluation of multiple, often conflicting, criteria such as geology, geotechnical stability, economic viability, environmental impact and social acceptability. Multi-Criteria Decision Making (MCDM) frameworks provide structured pathways for eliciting expert judgements, assigning weights to criteria and comparing candidate methods. Classical techniques such as the Analytic Hierarchy Process (AHP) and PROMETHEE enable pairwise comparisons and outranking to produce a ranked list of mining options. More recent advances incorporate fuzzy set theory to capture uncertainty in expert assessments and hybridise methods—for example combining fuzzy AHP with TOPSIS—to improve robustness. Sensitivity analysis remains a critical tool for testing the stability of results under variations in criteria weights or performance scores. Together, these approaches enhance transparency, support stakeholder engagement and guide the selection of mining methods that balance profitability, safety and sustainability on a global scale.

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Integrated AHP and PROMETHEE methods have been employed to structure the mining method selection problem into a hierarchical model of criteria and subcriteria. Experts assign relative weights via pairwise comparison, after which PROMETHEE generates a complete ranking of alternatives. A case study involving five underground mining methods demonstrated clear differentiation among options and used sensitivity analysis to confirm the robustness of the preferred solution under varying weight scenarios.

A fuzzy Analytic Hierarchy Process has been applied to the selection of underground mining methods where incomplete information and subjective judgements prevail. By expressing pairwise comparisons as fuzzy numbers, the approach captures ambiguity in expert input and computes aggregated weights for criteria such as rock mechanics, ventilation requirements and cost. The outcome is a more flexible decision framework that adapts to changing site conditions and expert consensus.

A novel fuzzy-environment model for mining method selection was developed in a regional case study of a coal deposit. This model extends conventional MCDM by integrating linguistic assessments of geological and operational factors within a fuzzy framework. The methodology demonstrated that handling imprecise data through fuzzy membership functions enhances consistency in ranking and offers decision-makers a transparent, interpretable tool tailored to local mining contexts.

Multi-Criteria Decision Making in Mining Method Selection publication trend

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Technical terms

Multi-Criteria Decision Making (MCDM): A collection of methods for evaluating and ranking alternatives based on multiple, often conflicting, criteria.

Analytic Hierarchy Process (AHP): A structured technique for organising decision problems into hierarchies and deriving numerical weights from pairwise comparisons of criteria.

PROMETHEE: An outranking method that ranks alternatives by comparing preference flows across all criteria, producing a complete or partial order of options.

Fuzzy Analytic Hierarchy Process: A variant of AHP in which comparisons are expressed as fuzzy numbers to account for uncertainty and vagueness in expert judgements.

Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS): A method that identifies alternatives closest to an ideal solution and farthest from a negative-ideal solution by computing distance measures in criteria space.

Sensitivity Analysis: A procedure for examining how changes in criteria weights or performance scores affect the stability of the ranking of alternatives.

References

1. Mining method selection by integrated AHP and PROMETHEE method. Anais da Academia Brasileira de Ciências (2012).
2. Application of Fuzzy Analytic Hierarchy Process to Underground Mining Method Selection. Symmetry (2020).
3. THE DEVELOPMENT OF A NOVEL MODEL FOR MINING METHOD SELECTION IN A FUZZY ENVIRONMENT; CASE STUDY: TAZAREH COAL MINE, SEMNAN PROVINCE, IRAN. Rudarsko-geološko-naftni zbornik (2017).