Evidence map›Paper›PMID 42409847›Full record

ArticleScientific reports2026

Appropriate fleet selection using dynamic multi-criteria decision making (case study: Gol-E-Gohar Mine No. 3).

Amirhossein Homayounfar, Farhad Samimi Namin

Abstract read
In one paragraph

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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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Amirhossein HomayounfarDepartment of Mining Engineering, Amirkabir University of Technology, Tehran, Iran. amirhossein.homayounfar@gmail.com.ORCID https://orcid.org/0009-0009-7458-5906
Farhad Samimi NaminDepartment of Mining Engineering, University of Zanjan, Zanjan, Iran. f.samiminamin@znu.ac.ir.ORCID https://orcid.org/0000-0002-7953-4843

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

ANPCarbon dioxide emissions reductionDMCDMEquipment selection

Identifiers

PMID42409847
PMCPMC13338193

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.