Abstract
A discrete Success-History based Adaptive Differential Evolution (SHADE) method has been developed and applied for fuel loading pattern (LP) optimization of a VVER-1000 reactor. SHADE uses an adaptive mechanism based on a historical record of successful control parameters, i.e., mutant scale F and crossover ratio CR, to improve the original differential evolution (DE) algorithm. Therefore, instead of three control parameters in the original DE, the SHADE method consists of two parameters of population size NP and memory size H. To apply the SHADE method to the fuel LP optimization, a relative position indexing approach was deployed to convert real variables into integer variables. Application of the discrete SHADE method to the problem of fuel LP optimization has been performed based on an VVER-1000 MOX core. A fitness function was chosen to maximize the keff, while flattening the radial power distribution. The results show that the keff of the optimal LP is greater than that of the reference core by about 1580 pcm. Whereas, the radial power peaking factor (PPF) of the optimal LP is about 2.4% smaller than that of the reference core.
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