The incorporation of the uncertainties of geometallurgical variables in mine planning provides new opportunities for decision-makers to analyse, compare and choose among many scenarios to achieve an optimal balance between economic and operational objectives. This research focuses on maximising economic return and minimising the risk arising from the uncertainty associated with geometallurgical variables. We formulate two-objective optimisation problems based on an underground mining operation. The first objective is the maximisation of the Net Smelter Return, which includes penalties associated with deleterious elements in concentrates. Four different objectives were tested as candidates for the second objective: Volatility, Value at Risk, Conditional Value at Risk and deviation from the planned production target. The first three are measures of economic risk and the fourth is a measure of operational risk. Uncertainties in metal grades, geometallurgical recoveries and grades in concentrate are included in the proposed model. Our results demonstrate that geometallurgical uncertainties can be successfully integrated into production scheduling optimisation in a multi-objective approach and the problem can be solved using genetic algorithms to yield useful conclusions to support the decision-making process.