Production schedules that provide optimal operating strategies while meeting practical,technical,and environmental constraints are an inseparable part of mining operations.Relying only on manual planning methods or computer software based on heuristic algorithms will lead to mine schedules that are not the optimal global solution.Mathematical mine planning models have been proved to be very effective in supporting decisions on sequencing the extraction of material in mines.The objective of this paper is to develop a practical optimization framework for caving operations’production scheduling.To overcome the size problem of mathematical programming models and to generate a robust practical near-optimal schedule,a multi-step method for long-term production scheduling of block caving is presented.A mixed-integer linear programming(MILP)formulation is used for each step.The formulations are developed,implemented,and verifed in the TOMLAB/CPLEX environment.The production scheduler aims to maximize the net present value of the mining operation while the mine planner has control over defned constraints.Application and comparison of the models for production scheduling using 298 drawpoints over 15 periods are presented. Production schedules that provide optimal operating strategies while meeting practical, technical, and environmental constraints are an inseparable part of mining operations. Relying only on manual planning methods or computer software based on heuristic algorithms will lead to mine schedules that are not the optimal global solution. Mathematical mine planning models have been proved to be very effective in supporting decisions on sequencing the extraction of material in mines. The objective of this paper is to develop a practical optimization framework for caving operations’ production scheduling. To overcome the size problem of mathematical programming models and to generate a robust practical near-optimal schedule, a multi-step method for long-term production scheduling of block caving is presented. A mixed-integer linear programming (MILP) formulation is used for each step. The formulations are developed, implemented, and verifed in the TOMLAB / CPLEX environment. The production scheduler aims to maximize the net present value of the mining operation while the mine planner has control over defned constraints. Application and comparison of the models for production scheduling using 298 drawpoints over 15 periods are presented.