Timely and effective maintenance scheduling is the key to the safe and stable operation in oil and gas fields. Large-scale maintenance tasks with multiple priorities are difficult to complete in an acceptable time. To accelerate computation, a two-layer strategy is proposed. At the upper layer, a lumped general task for each well cluster is generated. This lumping allows the upper layer model to concentrate on the urgent and important tasks, and thus a significantly reduced-scale mixed integer linear programming (MILP) model can be resulted to determine the dispatch and time length assigned for each technician. At the lower layer, a small-scale MILP model is established for each technician, utilizing the reserved time in the upper layer as the constraint. The results demonstrate that our approach significantly outperforms the complete MILP model in efficiency. The method is presently being implemented in real-world scenarios through our collaboration with the industry.

中文翻译：

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考虑多优先级的维修任务调度两层优化方法

及时有效的维护调度是油气田安全稳定运行的关键。具有多个优先级的大规模维护任务很难在可接受的时间内完成。为了加速计算，提出了两层策略。在上层，生成每个井簇的集中一般任务。这种集中使得上层模型可以集中精力处理紧急和重要的任务，从而可以得到规模显着缩小的混合整数线性规划（MILP）模型，以确定分配给每个技术人员的调度和时间长度。在下层，利用上层的预留时间作为约束，为每个技术人员建立一个小规模的MILP模型。结果表明，我们的方法在效率上明显优于完整的 MILP 模型。目前，我们正在与业界合作，在现实场景中实施该方法。