Robust optimization for mine planning

Fenemedre Qaeze (1) , Romain Guillaume (1, 2) , Caroline Thierry (1, 2)

1 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage
2 UT2J - Université Toulouse - Jean Jaurès

In this paper, we are interested in mine planning under uncertainty on the capacity of extraction in a mine complex. Indeed, in real life there is always a gap between planned activities and activities carried out during the period. In this paper, we focus on the activity of extraction. In order to achieve this challenge, we proposed a model to represent the mining complex. This model takes into account the uncertainty on the capacity by the use of scenarios. In order to face the uncertainty on the capacity of extraction we propose a robust approach with the MaxMin decision criterion. To the best of our knowledge, while the bulk of the literature treats the optimization in mining complex with stochastic approaches, this paper uses a robust approach under uncertainty. A case study using data from a nickel laterite company is used in order to implement the proposed model under uncertainty on capacity.

Mots clés: MaxMin criterion; Mine planning; Scenario; Uncertainty

Domaines: Intelligence artificielle [cs.AI]; Apprentissage [cs.LG]; Logique en informatique [cs.LO]; Informatique et langage [cs.CL]

Fenemedre Qaeze, Romain Guillaume, Caroline Thierry. Robust optimization for mine planning. 11ème Conférence Francophone de Modélisation, Optimisation et Simulation des Systèmes (MOSIM 2016), Aug 2016, Montréal, Canada. pp. 1-10. ⟨hal-01809274⟩