A decision support system and software tool (MMS-ANP) for mining method selection based on analytic network process

Articles in Press

Document Type : Research Paper

Authors

1 Mining and Metallurgical Engineering Department, Amirkabir University of Technology, Tehran, Iran.

2 Department of Mining Engineering, University of Zanjan, Zanjan, Iran.

10.22059/ijmge.2026.403807.595317

Abstract

Mining method selection is a critical and complex decision in mining design, heavily influencing project costs and operational efficiency. Traditional approaches to mining method selection often struggle with balancing accuracy and practicality, particularly due to the computational complexity and time demands of techniques like the Analytic Network Process (ANP). This paper introduces a novel desktop program, developed using Python, Cascading Style Sheets (CSS), Structured Query Language (SQL), and the Comprehensive Python Bindings for Qt v5 (PyQt5) framework, that integrates ANP with the University of British Columbia method (UBC) alongside unique insights from recent studies to enhance decision-making accuracy and speed. Unlike conventional approaches, our software automates the ANP method, overcoming its inherent complexity and enabling real-time comparisons of multiple conditions to determine the optimal mining method. By combining ANP's robust decision-making capabilities with the practical efficiency of the UBC method, our program provides a streamlined solution that significantly reduces computation time while maintaining high precision. This paper details the technical implementation, including the algorithm design and framework integration, and validates the software through case studies that highlight its superior performance in addressing complex mining scenarios.

Keywords

Main Subjects

References

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Available Online from 10 May 2026

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