如果量子超级计算机开发成功，那么对于解决某些问题，遗传算法将迅速成为不仅可行而且更优越的方法。
If quantum supercomputers are ever developed, genetic algorithms will suddenly become not only feasible, but preferable as an approach to solving certain problems.
遗传算法应用程序领域有无限的潜力。
The field of genetic algorithms applications has unlimited potential.
仿真还可以允许对机器人控制系统进行革新，这依赖于很多代控制系统的随机排列（遗传算法可以证实这一点）。
Simulation also allows the evolution of robotics control systems, which depend on random permutations of the control system over many generations (as demonstrated by genetic algorithms).
遗传算法模仿达尔文的自然选择，其中“适应性”选择进行生存、繁殖以及由此而来的适应性变异的个体。
Genetic algorithms mimic Darwinian natural selection, where "fitness" selects individuals for survival, breeding, and, hence, adaptive mutation.
在本文中，我将介绍有关Perl遗传算法更高级的内容。
In this article, I cover more advanced material on genetic algorithms in Perl.
Perl用于实现遗传算法的主要缺点在于速度慢。
如果您有兴趣在自己的应用程序中使用遗传算法，一定要研究MyBeasties(请参阅参考资料一节)。
Be sure to examine MyBeasties (see the Resources section) if you are interested in using genetic algorithms in your own applications.
在某种程度上，计算机病毒的传播方式早就表现出了与遗传算法的某些相似之处。
To some extent, virus infections already exhibit processes similar to genetic algorithms.
病毒发生的变化类似突变，又一个遗传算法的特征。
Variations of viruses are also similar to mutations, another factor in genetic algorithms.
说实话，在计算机科学的一些主要分支学科的命名上就可以看出生物学的影子，譬如人工神经网络，遗传算法和进化计算法等等。
Indeed, the names of major subfields of computer science-such as artificial neural networks, genetic algorithms, and evolutionary computation-attest to the influence of biological analogies.
在计算机学习用户程序中，Hadoop已经作为处理大量GA个体的规模遗传算法的一种方法(潜在解决方案)。
In machine learning applications, Hadoop has been used as a way to scale genetic algorithms for processing large populations of GA individuals (potential solutions).
然后，为了加快遗传算法的收敛速度减少算法执行时间引入模拟退火机制对上述算法进行优化。
Then the mechanism of Simulated Annealing is import in the algorithm above to decrease the execution time and quickens the velocity of convergence.
对于有时间窗的非满载VSP问题，将货运量约束和软时间窗约束转化为目标约束，建立了非满载VSP模型，设计了基于自然数编码，使用最大保留交叉、改进的反转变异等技术的遗传算法。
On the VSP with time window, while the restraints of capacity and time windows are changed into object restraints, a mathematic model is established.
实验证明，该算法不但可以有效地克服标准遗传算法的缺陷，而且计算速度、精度和算法稳定性也得到了显著提高。
The research results show that the algorithm can not only overcome the short comings of SGA effectively, but also evidently improve the computing speed, computing precision and stability.
实验证明，该算法不但可以有效地克服标准遗传算法的缺陷，而且计算速度、精度和算法稳定性也得到了显著提高。
The research results show that the algorithm can not only overcome the short comings of SGA effectively, but also evidently improve the computing speed, computing precision and stability.
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