Kumral M.2024-08-042024-08-0420119786050101034https://hdl.handle.net/11616/9238522nd International Mining Congress and Exhibition of Turkey, IMCET 2011 -- 11 May 2011 through 13 May 2011 -- 110210Mine production scheduling under uncertainty is one of main challenges in mining ventures. Since the values of coefficients in the optimization procedure are obtained in medium of sparse data, sampling and assaying errors, and unknown future events, the implementations based on the deterministic models may lead to destructive consequences to the mining company. In this paper, a robust stochastic optimization (RSO) approach is used to deal with mine production scheduling in a manner that the solution is insensitive to changes in input data. The model was demonstrated on a case study. It was observed that RSO could be executed to solve mine production scheduling problem under an uncertain environment efficiently.eninfo:eu-repo/semantics/closedAccessEconomic and social effectsOptimizationProduction controlDeterministic modelsInput datasMine planningMine productionMining companiesOptimization proceduresStochastic optimizationsUncertain environmentsSchedulingConference Object47532-s2.0-84923094760N/A