Multi-Objective Robust Optimization for Planning of Mineral Processing under Uncertainty

The planning of mineral processing is crucial for improving the utilization ratio of nonrenewable raw mineral resources. However, in the optimization process, the uncertainty of raw ore grade poses a very important issue and it directly affects the optimization performance. To address the above-mentioned issues, an improved multi-objective robust optimization algorithm is proposed, which employs NSGA-II as the basic component assisted by the random elite immigrant scheme and robustness evaluation in batches strategy. The proposed strategy aims at realizing the optimization of the planning of mineral processing. Using real data from a mineral processing plant on iron ore beneficiation process has been carried out. Experiment results show that the proposed strategy can efficiently achieve the Pareto front of the multi-objective robust optimization problem under the disturbance.