Abstract
In this paper we introduce a greedy randomized adaptive search procedure(GRASP) algorithm for solving a copper mine planning problem. In the last 10 years this real-world problem has been tackled using linear integer programming and constraint programming. Our mine planning problem is a large scale problem, thus in order to find an optimal solution using complete methods, the model was simplified by relaxing many constraints. We now present a Grasp algorithm which works with the complete model and it is able to find better feasible near-optimal solutions, than the complete approach that has been used until now.
Partially supported by the FONDEF Project: Complex Systems, and Fondecyt Project 1080110.
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Riff, MC., Otto, E., Bonnaire, X. (2009). A New Strategy Based on GRASP to Solve a Macro Mine Planning. In: Rauch, J., Raś, Z.W., Berka, P., Elomaa, T. (eds) Foundations of Intelligent Systems. ISMIS 2009. Lecture Notes in Computer Science(), vol 5722. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04125-9_51
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DOI: https://doi.org/10.1007/978-3-642-04125-9_51
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