A scalable approach to optimal block scheduling

A critical aspect of long-term open-pit mine planning consists in computing a production schedule based upon a block sequencing strategy. Such a schedule should specify when and if blocks should be extracted in such a way as to maximize NPV, while satisfying wall-slope and production capacity constraints. It is well known that this problem can be modeled with integer programming (IP). However, integer programming is not used in practice because the size of typical block models makes such problems intractable to standard IP solvers. In this article we describe a scalable IP-based methodology for solving very large (millions of blocks) instances of this problem. We show that embedding standard IP technologies in a local-search based algorithm we are able to obtain near-optimal solutions to large problems in reasonable time. This methodology has been tested in several mine wide block models. Biography Marcos Goycoolea obtained his PhD from the School of Industrial and Systems Engineering (ISYE) of Georgia Tech in 2006, and is currently an Assistant Professor at the Universidad Adolfo Ibañez School of Business in Santiago, Chile. He teaches Operations Management and Optimization to MBA and Graduate students and conducts research on integer programming methodologies and their application to natural resource management. His focus of research is on developing computational methods and software for large-scale optimization-based decision support systems. For more information visit his website at http://mgoycool.uai.cl.