Optimization of Ore Reclaim and Blending in Mine Stockpiles Using Mixed-Integer Linear Programming for Quality Control in Iron Ore Processing

This paper addresses the short-term planning problem of ore reclaim and blending in iron ore mining operations, focusing on minimizing quality deviations between mine and concentrator buffer stockpiles. Motivated by the complexity of large-scale systems where early decisions directly impact final product quality, we propose a mathematical model to optimize the quantities of ore reclaimed and transported to the concentrator. The objective is to minimize deviations from ideal quality reference values while satisfying strict inventory limits, stockpile capacities, conveyor belt constraints, and operational rules. The original nonlinear formulation, based on weighted average quality and absolute deviations, is linearized into a Mixed-Integer Linear Programming (MILP) model. Computational experiments using real industrial D+14 planning data demonstrate that this approach produces more stable ore grades and significantly reduces quality fluctuations compared to standard production maximization strategies. Ultimately, the model improves operational consistency and supports highly effective decision-making across the entire mining supply chain.