Optimizing Mineral Value Chain with Market Uncertainty Using Benders Decomposition

A Benders decomposition-based method is developed to simultaneously optimize the upstream and the downstream of a mineral value chain. Mining blocks representing mineral deposits are dynamically aggregated based on the dual solution of the sub-problem to reduce the complexity in the upstream mine production scheduling. The production schedule obtained based on the aggregated scheduling units is then improved through a moving-window amelioration method. By observing the results of a series of numerical tests, we show that the proposed method effectively optimizes a mineral value chain by synchronizing the upstream mine production scheduling and the downstream material flow and process planning. The results of the numerical tests also show that ignoring the market uncertainty can result in the underestimation of profitability because of the underestimated value of low-grade materials. In order to adapt to the existence of market uncertainty, the stochastic optimizer suggests a higher processing capacity investment in the processing plant and a different long-term mine production schedule