Abstract
Although the process of heap leaching is an established technology for treating minerals, such as copper, gold, silver, uranium and saltpeter, as well as remediating soil, no studies to date have investigated process optimization. This work presents a methodology for the design and planning of heap leaching systems to optimize the process. This methodology consists of the creation of a superstructure that represents a set of alternatives to search for the optimal solution; from this superstructure, a mixed integer nonlinear programming (MINLP) model was generated, and a BARON-GAMS solver was used to find the optimal solution. This method was applied to the extraction of copper from systems with one, two and three heaps, and the effects of copper price, ore grade and other variables were analyzed for each system. From the results, it can be concluded that this methodology can be used to optimize heap leaching processes, including planning and design issues.
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