Quantum evolutionary algorithm and tabu search in pressurized water reactor loading pattern design

Abstract Reactor-core loading pattern (LP) design aims to find an adequate arrangement of fresh and burnt fuel assemblies (FAs) such that fuel utilization can be maximized while meeting safety constraints. Since many possible patterns are to be evaluated, the task is difficult, and its difficulty grows exponentially with increasing number of FAs. As a result, manually searching for an adequate LP is prohibitively time-consuming, and an automated approach for LP design is essential. This paper proposes an automated approach for pressurized water reactor (PWR) LP design. The proposed approach, a two-stage scheme that combines quantum evolutionary algorithm (QEA) and tabu search (TS), simultaneously possesses the capabilities of exploration and exploitation and can be effectively employed for LP design with less computational load. To demonstrate the design capability of the proposed approach, a reference cycle of the Maanshan nuclear power plant (NPP) in Taiwan is selected. For the same cycle, LP design is performed solely with QEA as well for performance comparison. Results from several experiments illustrate the efficacy and performance of the proposed approach.

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