Title: A multi-step approach to long-term open-pit production planning

Authors: Mohammad Tabesh; Clemens Mieth; Hooman Askari-Nasab

Addresses: Mining Optimization Laboratory (MOL), School of Mining and Petroleum Engineering, Department of Civil & Environmental Engineering, University of Alberta, 7-109 Markin/CNRL Natural Resources Engineering Facility, Edmonton, Alberta, T6G 2W2, Canada ' Endeavour Financial Ltd., 37 Lombard Street, London, EC3V 9BQ, UK ' Mining Optimization Laboratory (MOL), School of Mining and Petroleum Engineering, Department of Civil & Environmental Engineering, University of Alberta, 3-133 Markin/CNRL Natural Resources Engineering Facility, Edmonton, Alberta, T6G 2W2, Canada

Abstract: The objective of this paper is to develop, verify, and present a multi-step methodology for three interrelated key components of open-pit mine planning: controlled optimal phase-design, characterisation of selective mining-units, and long-term production scheduling optimisation. A hybrid solution methodology for open-pit phase-design using integer programming and a local search heuristic is presented. Next, a hierarchical clustering approach with size and shape control, which aggregates blocks into minable polygons constrained within the pushback boundaries, is presented; and finally, a mixed integer linear programming mathematical model, which uses the generated pushbacks and aggregates as the planning units to provide near-optimal practical life-of-mine schedules, is introduced. In addition, the model inherently solves the cut-off grade optimisation problem. Two case-studies of real-size deposits are presented to illustrate practicality of the developed methodologies, and also to compare the results against industrial conventional practices to assess validity, performance, strengths, and limitations of the developed methodologies.

Keywords: aggregation; hierarchical clustering; mine production scheduling; mixed integer linear programming; MILP; pushback design; open pit production planning; long-term planning; optimal phase design; mathematical modelling; mining industry.

DOI: 10.1504/IJMME.2014.066577

International Journal of Mining and Mineral Engineering, 2014 Vol.5 No.4, pp.273 - 298

Available online: 26 Dec 2014 *

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