This paper addresses the optimization of long-term mine production schedules, building upon a previous stochastic integer programming (SIP) formulation based on surfaces, whereby the uncertain supply of metal is described by a set of equally probable orebody model representations. Surfaces are defined as limits that separate mining blocks assigned to two consecutive mine production periods. The proposed formulation maximizes discounted cash flows and minimizes the risk of deviating from production targets. The sequential implementation of previous work is considered herein for a pit space discretization followed by a yearly-based mine production scheduling, controlling the number of binary variables involved in the optimization processes and facilitating production scheduling for relatively large mineral deposits. The application of the sequential implementation of the proposed mathematical formulation in a relatively large gold deposit shows efficiency and improved results if compared with industry best practices, with a 43% higher ore production and a 19% increase in project net present value expectations.