Fleet Selection Optimized for Gol-E-Gohar Mine Using Dynamic Multi-Criteria Decision Making
A study focused on Gol-E-Gohar Mine No. 3 has introduced a dynamic multi-criteria decision-making (MCDM) approach to optimize fleet selection. This method aims to enhance operational efficiency by considering various factors that influence the choice of mining equipment. The research specifically addresses the complexities inherent in large-scale mining operations where equipment needs can fluctuate.
The dynamic MCDM framework allows for real-time adjustments and considerations, moving beyond static selection models. By integrating multiple criteria, such as cost, performance, availability, and environmental impact, the model provides a more robust and adaptable solution for fleet management. The application of this methodology at Gol-E-Gohar Mine No. 3 serves as a practical demonstration of its potential benefits in a real-world mining environment.
This research presents a methodological advancement in operational logistics for the mining sector, moving from static to dynamic decision-making frameworks. By incorporating multiple criteria, the approach acknowledges the complex interplay of economic, technical, and environmental factors in fleet selection. The focus on Gol-E-Gohar Mine No. 3 highlights the practical applicability of such models in large-scale resource extraction. Future developments could explore the integration of predictive analytics for equipment maintenance and lifecycle management, further enhancing the strategic value of dynamic fleet selection in the evolving landscape of industrial automation and resource management.
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