采用信息熵的自适应遗传算法为解决传统遗传算法容易早熟及收敛速度慢的缺陷，在分析了多样性的重要性后，提出了一种新的基于信息熵的遗传策略，该策略在保留最优个体的基础上，根据当前种群个体熵与种群熵的变化自适应调整遗传算子的各项参数，将种群的内部状态与遗传操作有机地结合起来，使得种群多样性得到保证，提高算法的全局搜索能力．试验结果表明了该方法在运行过程中能避免早熟的发生，在处理复杂问题时表现出较高的性能．To solve the problem of premature convergence and slow convergence flaws in the traditional genetic algorithm ，a new genetic strategy which is based on inform ation entropy is proposed based on analyzing the importance of the diversity．In this strategy，the algorithm will adaptively adj ust its operator parameters in accordance with the current individual entropy and the population entropy based on the reserved optim al individua1．It organically combines the internal state of population and the genetic operation to guarantee the diversity of the population and improve the global search capabilities．The result showed that this method can avoid the occurrence of premature convergence and provides excellent performance in dealing com plexproblems．
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