Abstract
The requirement for nuclear reactor decommissioning multi-objective optimization has grown in recent years. This paper proposes a dynamic total exposure dose estimation method based on the point-kernel method and improves its performance by introducing single-instruction-multiple-data and multi-threading technologies. Then, the dynamic dose estimating model is integrated into the non-dominated sorting genetic algorithm version 2 to obtain the preference-less path-order schemes for multi-objective decision-making. It is applied to a research reactor to validate its capability and analyze the optimized results. Results show the estimated dose conforms to the practically measured value, and the optimized schemes can significantly reduce the cumulative dose and the total path length objective. Besides, a frequency analysis recommendation based on the Pareto front is proposed to provide a non-weighting optimal decision. Hence, we suggest using this method to acquire optimal solutions and make further decisions for decommissioning.
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