映射交叉遗传算法在核动力设备优化设计中的应用

Application of Mapping Crossover Genetic Algorithm in Nuclear Power Equipment Optimization Design

摘要: 遗传优化算法(GA)已在核工程领域中得到广泛应用。本工作针对传统遗传算法(TGA)的缺点对其进行改进，得到映射交叉遗传算法(MCGA)并对MCGA算例进行测试。测试结果表明，MCGA较TGA具有更佳的优化性能。MCGA算法已被应用于反应堆冷却剂泵的优化设计中。

Abstract: Genetic algorithm (GA) has been widely applied in nuclear engineering. An improved method, named the mapping crossover genetic algorithm (MCGA), was developed aiming at improving the shortcomings of traditional genetic algorithm (TGA). The optimal results of benchmark problems show that MCGA has better optimizing performance than TGA. MCGA was applied to the reactor coolant pump optimization design.