Planning the maintenance of nuclear power plants is a complex optimization problem, involving a joint optimization of maintenance dates, fuel constraints and power production decisions. This paper investigates Mixed Integer Linear Programming (MILP) matheuristics for this problem, to tackle large size instances used in operations with a time scope of 5 years, and few restrictions with time window constraints for the latest maintenance operations. Several constructive matheuristics and a Variable Neighborhood Descent local search are designed. The matheuristics are shown to be accurately effective for medium and large size instances. The matheuristics give also results on the design of MILP formulations and neighborhoods for the problem. Contributions for the operational applications are also discussed. It is shown that the restriction of time windows, which was used to ease computations, induces large over-costs and that this restriction is not required anymore with the capabilities of matheuristics or local searches to solve such size of instances. Our matheuristics can be extended to a bi-objective optimization extension with stability costs, for the monthly re-optimization of the maintenance planning in the real-life application.

规划核电厂的维护是一个复杂的优化问题，涉及对维护日期，燃料约束和电力生产决策进行联合优化。本文研究了此问题的混合整数线性规划（MILP）数学方法，以解决在5年时间范围内使用的大型实例，并且对于最新维护操作几乎没有时间窗口约束的限制。设计了一些建设性的数学方法和可变邻域后裔局部搜索。事实证明，该数学方法对于中型和大型实例是有效的。数学方法还给出了针对该问题的MILP配方和邻域设计的结果。还讨论了对操作应用程序的贡献。结果表明，用于简化计算的时间窗口限制会导致大量的超额费用，并且借助数学或本地搜索功能来解决这种大小的实例，不再需要此限制。我们的数学可以扩展为具有稳定成本的双目标优化扩展，用于每月重新优化实际应用中的维护计划。