A Survey of Genetic Algorithm Applications in Nuclear Fuel Management
Palavras-chave:
Genetic Algorithm, Nuclear fuel management, Multi objective genetic algorithm, constrained optimization, Parallel genetic algorithm, Crossover, MutationResumo
The prime aim of nuclear fuel management is to achieve higher fuel utilization without compromising safety during reactor operation. Nuclear fuel management optimization is a classical nuclear engineering problem, which has been studied for more than four decades and several techniques have been used for its solution. Genetic algorithm is one among the major global optimization techniques, used in the field of nuclear fuel management. Aim of this paper is to survey genetic algorithm related developments happened during the last few decades in nuclear fuel management optimization. The objectives of this survey are: (i) to summarize how genetic algorithm is applied to the field of nuclear fuel management (ii) to compare different genetic algorithm techniques and operators used in solving the nuclear fuel management optimization problems (iii) to bring out current trends and future directions in this field. The survey will help the researchers in the field to get an overview about genetic algorithm techniques available for nuclear fuel management optimization and how to use them.Keywords: Genetic Algorithm, nuclear fuel management, multi objective genetic algorithm, constrained optimization, parallel genetic algorithm, crossover, mutation
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