Long-term block scheduling is a challenging problem that involves determining the best extraction period for blocks to maximize the net present value of the open-pit mining business. This process involves multiple constraints, mainly ensuring safe pit walls and imposing maximum limits on operational resource consumption. However, most of the models proposed in the literature do not sufficiently consider geometric constraints that ensure a minimum space for mining equipment to operate safely. These models overlook practical and operational constraints and generate solutions that are difficult to implement. Consequently, the promised net present value cannot be achieved. In this paper, we propose an integer linear programming model that considers minimum mining width requirements along with a decomposition heuristic method to solve it.The proposed model determines which blocks should be mined and when to maximize net present value while ensuring safe pit walls and respecting limits on operational resources and geometric constraints. Geometric constraints require that the minimum operational distance be considered within each extraction period. Because the incorporation of geometric constraints in the proposed model makes it harder to solve, a time-space decomposition heuristic is implemented. This heuristic consists of successive time and space aggregation/disaggregation to generate simpler subproblems to be solved. This approach was applied on two case studies. The results show that the proposed methodology generates practical production plans that are more realistic to implement in mining operations, lowering the gap between factual and promised net present value.

长期区块调度是一个具有挑战性的问题，涉及确定区块的最佳开采周期，以最大化露天采矿业务的净现值。这个过程涉及多重约束，主要是确保坑壁安全并对运营资源消耗施加最大限制。然而，文献中提出的大多数模型没有充分考虑确保采矿设备安全运行的最小空间的几何约束。这些模型忽视了实际和操作上的限制，并产生了难以实施的解决方案。因此，承诺的净现值无法实现。在本文中，我们提出了一种整数线性规划模型，该模型考虑最小采矿宽度要求以及分解启发式方法来解决该问题。所提出的模型确定应该开采哪些区块以及何时最大化净现值，同时确保安全坑壁并尊重运营资源和几何约束的限制。几何约束要求在每个提取周期内考虑最小操作距离。由于所提出的模型中几何约束的结合使得求解变得更加困难，因此实施了时空分解启发式。这种启发式方法由连续的时间和空间聚合/分解组成，以生成更简单的要解决的子问题。该方法应用于两个案例研究。结果表明，所提出的方法生成了在采矿作业中更现实的实际生产计划，从而缩小了实际净现值与承诺净现值之间的差距。