Whittier, M, Hauta, R & Fava, L 2017, 'Robust mine schedule optimisation', in M Hudyma & Y Potvin (eds), UMT 2017: Proceedings of the First International Conference on Underground Mining Technology, Australian Centre for Geomechanics, Perth, pp. 533-545, https://doi.org/10.36487/ACG_rep/1710_43_Whittier
(https://papers.acg.uwa.edu.au/p/1710_43_Whittier/)
Abstract: The identification of high-value, practical mine plans is a complex and challenging process. Mineral prices are a crucial factor to the value of a project and, due to the inherent volatility of the commodities market, also the most uncertain. Despite this reality, conventional planning processes don’t sufficiently account for the financial uncertainty associated with mining assets. As a consequence, life-of-mine schedules must often be extensively revisited as the fiscal climate changes. The inherent financial uncertainty of mining projects presents a substantial risk to stakeholders and without proper mitigation can easily reduce the perceived and real value of a mining asset.
The risks associated with uncertainty can be mitigated through the creation of robust mine schedules. In this paper, two distinct approaches to creating robust, optimised long-term underground mine schedules will be presented. The Genetic Optimizer for Stochastic Problems (GOSP) method incorporates price distributions, rather than fixed projections, into the optimisation process. The Horizon method incorporates the concept of ’management flexibility’ into the process of schedule optimisation. As will be demonstrated by a case study, these methods, when integrated with the Schedule Optimization Tool (SOT), produce robust, high net present value schedules for underground mining operations.

Keywords: robust mine planning, schedule optimisation, financial uncertainty, genetic algorithm