混合遗传算法在压水堆换料优化中的应用  

New Hybrid Optimization Method and Its Application to Pressurized Water Reactors Reloading Optimization

作　　者：王涛[1] 谢仲生[1] 

机构地区：[1]西安交通大学能源与动力工程学院,西安710049

出　　处：《西安交通大学学报》2005年第5期522-525,共4页Journal of Xi'an Jiaotong University

摘　　要：针对遗传算法和禁忌搜索算法的优点与缺陷,提出了遗传算法与禁忌搜索算法相结合的混合优化算法.该混合优化算法结合了遗传算法在全局搜索上的优点和禁忌搜索算法在局部搜索方面的优点,与标准遗传算法相比,在搜索能力和收敛速度上都有较大提高.为验证其优越性,使用国际原子能机构IAEA公布的Kalinin 5核电厂WWER 1000型堆芯第二循环换料基准题以及秦山第六循环堆芯换料问题进行了优化计算比较与校验.结果表明,遗传算法和禁忌搜索相结合的混合优化算法比单独使用遗传算法能够获得更好的堆芯布置方案,获得了更大的适应值,循环寿期增加了20 d,并且收敛速度也有所提高.A new hybrid optimization method (GATB) is proposed, which combines the genetic algorithm (GA) with the tabu search (TABU). The hybrid method adopts global search advantage of the GA and local search advantage of the TABU, and it possesses improved ability and convergence speed. The proposed hybrid method was implemented to the reactor reloading optimization calculation of WWER-1000 type reactor and Qinshan-I nuclear power plant core reloading. For verifying the advantages of this method, The reloading optimization calculations were performed by GATB and GA respectively using same fitness function and control parameters. The numerical results show that the hybrid optimization method converges faster and obtains better solution than GA.

关 键 词：遗传算法 禁忌搜索算法 混合优化法 六角形 

分 类 号：TL421[核科学技术—核技术及应用]