遗传算法的临界参数是 :初始群体大小,变异率,迭代步数,例如繁殖数等.在这课题中,初始群体大小是50,交叉率是1.0,变异率是0.1,采取了每个16的变动及2500的迭代数的数位.优化历史包括翘曲历程显示在数字7.遗传算法在约250个迭代步数后聚集于最优化,优化历史仅上升至250个迭代步数就证明到数字7 .翘曲值域在参考各点的优化值先后被合并在列表6.如列表6所示,翘曲值在大多数参考点明显减少,尽管他们在某些点略微增长.当考虑到最大翘曲度时,看来在灯基模型上,最大翘曲度在最优化前的2.47mm,有46.5%的几率在最优化后就减少到1.32mm .在列表6中,(-)和(无符号,也就是+)值域表示翘曲度在各自的参考点的减少和增加.
英语翻译Critical parameters of a genetic algorithm are size of t
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