The risk-averse ultimate pit problem
Canessa
G
author
Moreno
E
author
Pagnoncelli
B
K
author
2021
English
In this work, we consider a risk-averse ultimate pit problem where the grade of the mineral is uncertain. We derive conditions under which we can generate a set of nested pits by varying the risk level instead of using revenue factors. We propose two properties that we believe are desirable for the problem: risk nestedness, which means the pits generated for different risk aversion levels should be contained in one another, and additive consistency, which states that preferences in terms of order of extraction should not change if independent sectors of the mine are added as precedences. We show that only an entropic risk measure satisfies these properties and propose a two-stage stochastic programming formulation of the problem, including an efficient approximation scheme to solve it. We illustrate our approach in a small self-constructed example, and apply our approximation scheme to a real-world section of the Andina mine, in Chile.
Ultimate pit
Mining
Risk-averse optimization
Integer programming
WOS:000557140000001
exported from refbase (show.php?record=1219), last updated on Thu, 04 Nov 2021 18:10:41 -0300
text
10.1007/s11081-020-09545-4
Canessa_etal2021
Optimization And Engineering
Optim. Eng.
2021
Springer
continuing
periodical
academic journal
22
2655
2678
1389-4420