Malaki, S, Khodayari, F, Pourrahimian, Y & Liu, WV 2017, 'An application of mathematical programming and sequential Gaussian simulation for block cave production scheduling', in M Hudyma & Y Potvin (eds), UMT 2017: Proceedings of the First International Conference on Underground Mining Technology, Australian Centre for Geomechanics, Perth, pp. 323-337, https://doi.org/10.36487/ACG_rep/1710_25_Pourrahimian
(https://papers.acg.uwa.edu.au/p/1710_25_Pourrahimian/)
Abstract: The current trend of deeper and lower-grade deposits makes open pit mining less profitable. Mass mining alternatives have to be developed if mining at a similar rate is to be continued. Block cave mining is becoming an increasingly popular mass mining method, especially for large copper deposits currently being mined with open pit methods.
After finding the initial evaluation of a range of levels for starting the extraction of block cave mining, production scheduling plays a key role in the entire project’s profitability. Traditional long-term mine planning is based on deterministic orebody models, which can ignore the uncertainty in the geological resources.
The purpose of this paper is to present a methodology to find the optimal extraction horizon and sequence of extraction for that horizon under grade uncertainty. The model does not explicitly take into account other potential project value drivers such as waste ingress into the draw column or the impact of primary or secondary fragmentation on either production or recovery. Maximum net present value (NPV) is determined using a mixed-integer linear programming (MILP) model after choosing the optimum horizon of extraction given some constraints such as mining capacity, production grade, extraction rate and precedence. Application of the method for block cave production scheduling using a case study over 15 periods is presented.

Keywords: block caving, grade uncertainty, sequential Gaussian simulation, production scheduling