Direct sequencing of blocks in stochastic models with multi-mines and multi-destinations

Abstract Mining Scheduling is the one that maximizes profit from mining over time. By means of computational methods, the deposit is discretized in blocks and algorithms are used to consummate this objective. The methods that are widely known nowadays for mining scheduling optimization of a discrete block model were based on graph theory, and among those most used by the mining industry is a solution found by Lerchs and Grossmann (1965) which, together with other methods, was consolidated as the process of traditional mining planning. For both supply and multi-destination models, there is a limitation of the current methodology, since it consists of the optimization of each mine separately which may not be a global optimization solution. This article proposes an optimization of the benefit in a stochastic model through the DBS (Direct Block Scheduling) for a copper mining complex with two mines, a pre-existing copper stockpile and two treatment streams, comparing several scenarios and analyzing the best alternative for the proposed problem.