A two-layer optimization method for maintenance task scheduling considering multiple priorities

Abstract

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.