Global optimization for mining complexes aims to generate a production schedule for the various mines\nand processing streams that maximizes the economic value of the enterprise as a whole. Aside from the\nlarge scale of the optimization models, one of the major challenges associated with optimizing mining\ncomplexes is related to the blending and non-linear geo-metallurgical interactions in the processing\nstreams as materials are transformed from bulk material to refined products. This work proposes a\nnew two-stage stochastic global optimization model for the production scheduling of open pit mining\ncomplexes with uncertainty. Three combinations of metaheuristics, including simulated annealing, particle\nswarm optimization and differential evolution, are tested to assess the performance of the solver.\nExperimental results for a copper-gold mining complex demonstrate that the optimizer is capable of\ngenerating designs that reduce the risk of not meeting production targets, have 6.6% higher expected\nnet present value than the deterministic-equivalent design and 22.6% higher net present value than an\nindustry-standard deterministic mine planning software.
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