We propose a continuous-time scheduling model for the logistic and blending operations of copper concentrates with uncertain composition. The formulation, based on the Multi-Operation Sequencing (MOS) model, gives rise to a large-scale nonconvex mixed-integer nonlinear programming (MINLP) model. We adopt a two-step MILP-NLP decomposition strategy and enhance the MILP relaxation to propose schedules that significantly reduce the optimality gaps. The bounded uncertainty in element composition of the concentrates is addressed by an extended robust MOS model, which combines robust optimization and flexibility analysis techniques. The effectiveness of the models and the solution strategy is validated with an illustrative example and an industrial case study.

我们为不确定成分的铜精矿的物流和混合操作提出了连续时间调度模型。该公式基于多操作排序（MOS）模型，从而产生了大规模的非凸混合整数非线性规划（MINLP）模型。我们采用两步式MILP-NLP分解策略，并增强MILP弛豫，以提出可显着减少最佳差距的计划。通过扩展的鲁棒MOS模型解决了精矿元素组成的有限不确定性，该模型结合了鲁棒优化和灵活性分析技术。通过一个示例性实例和一个工业案例研究验证了模型和解决方案策略的有效性。