Abstract
Based on the genetic algorithm for solving multi-objective optimization easily leads to the defect of premature and slow convergence, so an improved niche genetic algorithm is proposed. This algorithm is to select distance parameter equals to the minimum Euclidean distance between the best individuals, using the method of allele comparison to determine within the distance parameter individuals whether similar. Using this method solves the problem of multi-objective optimization, which can produce a better niche environment, greatly protect the diversity of population and improve the search efficiency. The simulation results show that new algorithm effectively avoids falling into local optimal solutions, and performance is superior to the existing algorithms.
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