In this article we consider how to construct schedules for the stacking and reclaiming activities of high-throughput dry-bulk export terminals (DBET) that operate large machines called stacker-reclaimers (SR) and handle iron ore, coking coal and thermal coal for export. In terminals with large and persistent stockpiles, the ever-changing geometry of stockpiles can impose challenging scheduling constraints. For those situations, we propose that each stockpile is modelled in detail, for instance as a collection of heterogeneous sized blocks. This is called a bench block model (BBM). We then demonstrate how stockpiles are manipulated via their BBM and how BBM can be integrated as a form of stockpile manager within a sophisticated DBET scheduling engine. Numerical testing of the DBET scheduling engine and three horizontal bench block model (HBBM) has been performed and indicates that the application of BBM is worthwhile, if not essential. The concept of BBM is generic, highly flexible, and integrable into existing optimisation routines. The results provided are superior to other approaches that model stockpiles as simple silos. We can provide schedules that are devoid of any stockpile geometry errors in contrast to others which cannot, and computational overheads to do this are no greater than previous approaches. In the three case studies considered, it was also pleasing to see that solutions of comparable quality with key performance criteria (KPI) equivalent to those constructed without any consideration of stockpile geometry are achievable. The new scheduling approach can significantly reduce the time to perform terminal planning and can increase the utilization of key resources within the terminal.

在本文中，我们将考虑如何构建高吞吐量干散货出口码头（DBET）的堆放和回收活动时间表，该码头运行称为堆高回收机（SR）的大型机器并处理铁矿石，炼焦煤和动力煤进行出口。在拥有大量持久存货的码头中，不断变化的存货几何形状可能会带来具有挑战性的调度约束。对于这些情况，我们建议对每个库存进行详细建模，例如，将其作为不同大小的块的集合。这称为基准块模型（BBM）。然后，我们演示如何通过其BBM来操纵库存，以及如何将BBM作为一种库存管理器形式集成到复杂的DBET调度引擎中。DBET调度引擎的数值测试和三个卧式台架模型（HBBM）已执行，并且表明BBM的应用是必要的，即使不是必须的。BBM的概念是通用的，高度灵活的，并且可以集成到现有的优化例程中。提供的结果优于将库存建模为简单筒仓的其他方法。与其他计划相比，我们可以提供没有任何库存几何错误的计划，并且这样做的计算开销不会比以前的方法大。在所考虑的三个案例研究中，令人高兴的是，可以实现质量相当，关键性能指标（KPI）与不考虑库存几何形状的情况下等效的解决方案。