Optimization of a boiling water reactor loading pattern using an improved genetic algorithm

Yoko Kobayashi, Eitaro Aiyoshi

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


A search method based on genetic algorithms (GA) using deterministic operators has been developed to generate optimized boiling water reactor (BWR) loading patterns (LPs). The search method uses an Improved GA operator, that is, crossover, mutation, and selection. The handling of the encoding technique and constraint conditions is designed so that the GA reflects the peculiar characteristics of the BWR. In addition, some strategies such as elitism and self-reproduction are effectively used to improve the search speed. LP evaluations were performed with a three-dimensional diffusion code that coupled neutronic and thermal-hydraulic models. Strong axial heterogeneities and three-dimensional-dependent constraints have always necessitated the use of three-dimensional core simulators for BWRs, so that an optimization method is required for computational efficiency. The proposed algorithm is demonstrated by successfully generating LPs for an actual BWR plant applying the Haling technique. In test calculations, candidates that shuffled fresh and burned fuel assemblies within a reasonable computation time were obtained.

Original languageEnglish
Pages (from-to)144-151
Number of pages8
JournalNuclear Technology
Issue number2
Publication statusPublished - 2003 Aug


  • Boiling water reactor
  • Genetic algorithm
  • Loading pattern

ASJC Scopus subject areas

  • Nuclear and High Energy Physics
  • Nuclear Energy and Engineering
  • Condensed Matter Physics


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