Application of Fuzzy Analytic Hierarchy Process to Underground Mining Method Selection

Sanja Bajić,Dragoljub Bajić,Vesna Ristić Vakanjac,Branko Gluščević

doi:10.3390/sym12020192

Abstract

The paper proposes a problem-solving approach in the area of underground mining, related to the evaluation and selection of the optimal mining method, employing fuzzy multiple-criteria optimization. The application of fuzzy logic to decision-making in multiple-criteria optimization is particularly useful in cases where not enough information is available about a given system, and where expert knowledge and experience are an important aspect. With a straightforward objective, multiple-criteria decision-making is used to rank various mining methods relative to a set of criteria and to select the optimal solution. The considered mining methods represent possible alternatives. In addition, various criteria and subcriteria that influence the selection of the best available solution are defined and analyzed. The final decision concerning the selection of the optimal mining method is made based on mathematical optimization calculations. The paper demonstrates the proposed approach as applied in a case study.

Highlights

It is well-known that in most cases, a large number of criteria and subcriteria for decision-making matrices are uncertain and decision makers are unable to arrive at exact numerical values for comparing decisions
Scientists worldwide have introduced a number of new theories and procedures for selecting underground mining methods, which generally involve gray correlation and multiple-criteria decision-making (AHP, fuzzy analytic hierarchy process (FAHP), TOPSIS, PROMETHEE, ELECTRE, and VIKOR)
Bogdanovic et al [16] employed a combination of AHP and PROMETHEE to select the most suitable mining method for the Čoka Marin underground mine in Serbia: AHP to analyze the structure of the problem and determine criteria weights, and PROMETHEE

Summary

Introduction

It is well-known that in most cases, a large number of criteria and subcriteria for decision-making matrices are uncertain and decision makers are unable to arrive at exact numerical values for comparing decisions. Balusa & Gorai [14] compare mining methods using five MCDM models (TOPSIS, VIKOR, ELECTRE, PROMETHEE II, and WPM) They employed AHP to determine the weights of effective criteria for the Tummalapalle uranium mine in India. Bogdanovic et al [16] employed a combination of AHP and PROMETHEE to select the most suitable mining method for the Čoka Marin underground mine in Serbia: AHP to analyze the structure of the problem and determine criteria weights, and PROMETHEE for final ranking and sensitivity analysis. Yazdani-Chamzini et al [18] proposed a selection model for the optimal mining method at the Angouran mine, one of the main producers of zinc in Iran They developed the model based on FAHP and FTOPSIS. The optimal solution involves the shortest mining time and the lowest consumption of energy and materials, along with full safety at work and no adverse effect on mine development

Case Study

Methodology

Results and Discussion