Multi-Objective Evolution Algorithm Based on Improved Crowding-distance

TL;DRAbstract

In terms of the inadequacy of Multi-Objective Evolution Algorithm(MOEA) with the crowding-distance truncation operator to preserve the distribution and the deficiency of the distribution that is hard to get near to the true Pareto front under the binary condition,an improved MOEA is proposed.The improved algorithm includes the improved crowding-distance truncation operator and the self-adaptive mutation operator.Compared to other classical MOEA,experiment analysis proves that the improved algorithm achieving the final Pareto solutions qualified the better convergence and the good distribution to the true Pareto front.

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