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An interval bound algorithm of optimizing reactor core loading pattern by using reactivity interval schema

ANNALS OF NUCLEAR ENERGY 2011年第12期38卷 2787-2796页

作者： Gong, Zhaohu Wang, Kan Yao, Dong Tsinghua Univ Dept Engn Phys Beijing 100084 Peoples R China Nucl Power Inst China Sci & Technol Reactor Syst Design Technol Lab Chengdu 610041 Sichuan Peoples R China

In order to optimize the core loading pattern in Nuclear Power Plants, the paper presents a new optimization method - interval bound algorithm (IBA). Similar to the typical population based algorithms, e.g. genetic algorithm, IBA maintains a population of solutions and evolves them during the optimization process. IBA acquires the solution by statistical learning and sampling the control variable intervals of the population in each iteration. The control variables are the transforms of the reactivity of fuel assemblies or the worth of burnable poisons, which are the crucial heuristic information for loading pattern optimization problems. IBA can deal with the relationship between the dependent variables by defining the control variables. Based on the IBA algorithm, a parallel Loading Pattern Optimization code, named IBALPO, has been developed. To deal with multiple objectives and constraints, the Dynamic Discontinuous Weight Factors (DDWF) for the fitness function have been used in IBALPO. Finally, the code system has been used to solve a realistic reloading problem and a better pattern has been obtained compared with the ones searched by engineers and genetic algorithm, thus the performance of the code is proved. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Loading Pattern Optimization interval bound algorithm Multi-objective optimization Dynamic Discontinuous Weight Factors Reactivity

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