A multi-objective Fuzzy Robust Optimization model for open-pit mine planning under uncertainty

In open-pit mines, transporting ore from the pit to unloading sites is one of the most significant factors driving both cost and environmental impact. However, uncertainty in truck arrival times and ore transport rates due to varying weather conditions, physical limitations, and mental states of the workforce makes efficient allocation a challenge. This study addresses this challenge by proposing a multi-objective mathematical model that optimizes cost, production, and environmental objectives. Fuzzy Robust Optimization (FRO) incorporates uncertainty into the model, and the Linear Programming Metric (LP-Metric) is employed to solve it. A case study using the Chadormalu mine demonstrates the model's effectiveness in planning shift transport. Sensitivity analysis confirms the model's ability to handle uncertainty. Notably, the optimality robustness factor solely influences the objective function's value (representing the sum of relative deviations from optimal function values). Feasibility robustness, however, has no impact on any measurements.