ArticleScientific reports2026
Appropriate fleet selection using dynamic multi-criteria decision making (case study: Gol-E-Gohar Mine No. 3).
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The growth of large-scale mining operations presents challenging choices when selecting loading and transport equipment, as these decisions significantly impact output, expenditure, and ecological footprint; poor choices can lead to delays, increased fuel consumption, higher pollution, or damaged equipment. Because mining environments are constantly evolving, decisions must be precise, adaptable, and timely; however, past research has often overlooked the inclusion of time factors and lifecycle phases in fleet planning. This work presents a flexible decision-making method using the Analytic Network Process (ANP) at Gol-E-Gohar Iron Mine No. 3. Its main new feature is that it divides the mine's lifespan into three periods (start-up, middle phase, and final stage) to track how priorities shift over time. For each phase's key factors, insights were gathered from 25 mining experts (from universities and industry) through side-by-side evaluations. To enhance consistency while mitigating characteristics or peculiarities associated with phase-only reviews, another Total Mine Life (TML) setup is calculated as a reference point, influencing how technical, financial, and ecological factors are evaluated and assessed at each stage. Instead of relying solely on averages, every ANP comparison, supermatrix run, ranking outcome, and sensitivity check was handled via SuperDecisions software, which also delivered the TML and split-phase outputs used for comparison. Findings show that, compared to fixed methods, the shifting method is more effective or performs better, adjusts more easily, and is more logical or coherent, matching choices to the real-world demands of each interval, so cutting costs and easing ecological strain. In the Gol-E-Gohar No. 3 example, the fleet was first reviewed using the TML benchmark, then across three time blocks, revealing how breaking it into phases helps select suitable equipment or appropriate tools actual conditions at every turn.
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