MULTI-OBJECTIVE OPTIMIZATION OF FUEL RELOADING PATTERNS FOR RESEARCH REACTORS BY GENETIC ALGORITHMS
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Abstract
This paper presents an application of a genetic algorithm (GA) to the fuel reload optimization for a research reactor. In this work, a model of the problem and a new coding procedure for the GA to automatically search for optimal fuel loading patterns most suitable for the research reactor is proposed. The objective function maximizes the effective multiplication factor and minimizes the power peaking factor. The GA works with an elitist selection based on the elitism strategy and the roulette wheel spin method, a modified one-point crossover and a simple mutation. Results from illustrative calculations for the Dalat research reactor show that the GA can successfully search for the optimal loading patterns, which can be employed in a practical refueling operation.
Article Details
Keywords
Research reactor, fuel reload optimization, genetic algorithms, elitism strategy
References
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