备品备件是核电厂设备检修的物质基础，然而持有过量的备件库存将增加核电厂运营成本，通过设置合理的备件库存参数，在保障供应和控制库存之间寻找到一个合理的平衡点。针对核电备件库存参数设置问题，将遗传算法引入备件库存参数优化领域。通过建立核电备件库存参数评价方法，将核电备件库存参数设置转换为多变量优化问题，使用遗传算法计算最优库存参数。选用大亚湾核电厂的备件进行仿真测试，当给备件增加多种领用波动时，使用遗传算法计算的备件库存参数均优于当前数据库中的库存参数，结果表明遗传算法应用到备件库存参数优化领域具有重要的实用价值。

Spare parts are the material basis for equipment maintenance in nuclear power plants. However, holding excessive spare parts inventory will increase the operating cost of nuclear power plants. By setting reasonable spare parts inventory parameters, a reasonable balance between supply guarantee and inventory control can be found. To solve the problem of spare parts inventory parameter setting, genetic algorithm was introduced into the field of spare parts inventory parameter optimization. By establishing the evaluation method to evaluate the quality of spare parts inventory parameters, the setting of spare parts inventory parameters was transformed into a multivariable optimization problem, and the genetic algorithm was used to calculate the optimal inventory parameters. The spare parts of nuclear power plants were selected for simulation testing. When the spare parts are added with multiple consumption fluctuations, the spare parts inventory parameters calculated by genetic algorithm are better than those in the current database. The results show that genetic algorithm has important practical value in the field of spare parts inventory parameter optimization.