Strategic Long-Term Planning for Sublevel Caving: A Unified Mixed-Integer-Linear Programming Framework for Development, Ventilation, Production Scheduling, and Stockpile Management

In typical underground mine planning models, development activities and the downstream flow of materials are treated as distinct operations from ore extraction sequencing. Sublevel caving (SLC) includes development, stockpiling, and production, each occurring independently on different levels. To im...

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Vydané v:Mining, metallurgy & exploration Ročník 42; číslo 3; s. 1741 - 1757
Hlavní autori: Khazaei, Soroush, Mousavi, Amin, Pourrahimian, Yashar
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Cham Springer International Publishing 01.06.2025
Predmet:
Engineering
Materials Engineering
Metallic Materials
Mineral Resources
Long-term mine planning
GEMS PCSLC
Mixed-integer-linear-programming
Sublevel caving
ISSN:2524-3462, 2524-3470
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Popis
Shrnutí:In typical underground mine planning models, development activities and the downstream flow of materials are treated as distinct operations from ore extraction sequencing. Sublevel caving (SLC) includes development, stockpiling, and production, each occurring independently on different levels. To improve planning efficiency, it is crucial to integrate these simultaneous activities into a holistic model. However, most studies on SLC scheduling primarily focus on ore extraction sequencing, often neglecting the interplay between different activities. This study addresses the gap by introducing an integrated mixed-integer linear programming (MILP) framework, implemented in Python using PuLP and CPLEX, to optimize production, development, and control material flow between the mine, plant, and stockpile. The model aims to maximize net present value (NPV) while accounting for key operational constraints, including development activities, mining and processing capacities, continuous mining, limits on active and newly added mining units (MUs), grade control, sequencing precedences, and stockpile management. It schedules MUs across production areas and levels and optimizes material flow by prioritizing direct transfer from the mine to the plant to avoid rehandling costs while ensuring the plant’s average head grade remains within limits. The proposed framework was verified through an optimization process and applied to a real-world SLC iron mine with 367 MUs over 23 periods, demonstrating the practicality of the integrated model. By accounting for mining direction and all SLC constraints, including operational limitations, the model achieved an NPV of 1.94 B$.
ISSN:2524-3462
2524-3470
DOI:10.1007/s42461-025-01235-y