An enhanced integer coded genetic algorithm to optimize PWRs

被引：34
|
作者：
Norouzi, A. [1 ]
Zolfaghari, A. [1 ]
Minuchehr, A. H. [1 ]
Khoshahval, F. [1 ]
机构：
[1] Shahid Beheshti Univ, Dept Engn, GC, Tehran, Iran
来源：
PROGRESS IN NUCLEAR ENERGY | 2011年 / 53卷 / 05期
关键词：
Fuel management; Optimization; GA; Integer coded genetic algorithm; Mutation; WWER-1000;
D O I：
10.1016/j.pnucene.2011.03.005
中图分类号：
TL [原子能技术]; O571 [原子核物理学];
学科分类号：
0827 ; 082701 ;
摘要：
The aim of this work is to develop a new hybrid mutation integer for integer coded genetic algorithm, ICGA, to design the loading pattern, LP, in pressurized water reactors. Because of the huge number of possible combinations for the fuel assemblies, FAs, loading in a core and finding the optimum solution is a truly complex problem. In common genetic algorithms the mutation and crossover techniques are used to optimize an objective function. In this study flattening of power inside a reactor core is chosen as an objective function. To obtain optimal FA arrangement an Enhanced Integer Coded Genetic Algorithm, EICGA, is developed in order to obtain an optimal FA arrangement. This code is applicable to all types of PWR cores having different geometries and designs with many number of FA types. The results show a marked improvement in comparison to published data. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：449 / 456
页数：8
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