在我没有编写的框架中， Jenes 可能是拥有我最喜欢的 API 的框架的样子。它也使用更现代的基于泛型的方法。
I wrote the Watchmaker Framework so my opinions are not unbiased. ECJ and JGAP are the two most established options and probably the most comprehensive. On the other hand their age means they target older versions of Java, which means no generics.
The Hidden Clause blog did a series of posts (scroll down the list to see them) comparing JGAP, ECJ and Watchmaker.
Of the frameworks I didn't write, Jenes is probably the one that has the API that I most like the look of. It too uses a more modern generics-based approach.
也许您会看看我写的 GA (Jenetics)。它使用 Javolution 库进行并行化，使用 JScience 库进行数字处理。我认为值得一看。
Maybe you will have a look at the GA (Jenetics) that I've written. It uses the Javolution library for parallelization and the JScience library for the numeric stuff. I think it's worth a look.
I know Apache Mahout (based on Apache Hadoop) has a load of machine learning type algorithms - although not sure if it's exactly what you're looking for?
This is an alternative I had bookmarked for my own edification later. I've used JGAP in the past and been happy with it, but this one seems to have lots of excellent examples and I thought I'd give it a try next time I needed optimization code.
Check out Apache Math - Genetics Algorithm. I have started to look at it. As I'm new to Genetics Algorithms, not sure of the comprehensiveness or not of this library. It does have a nice licensing model for multiple uses for academic and commercial use (Apache 2.0).
GALib, Java Genetic Algorithm (JAR) library, models chromosomes as real numbers, characters, strings, and string sequences. Very easy to use, just extend one of the existing GA classes and implement your fitness function. Sample GAs included.
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我编写了 Watchmaker Framework，因此我的观点并非公正。 ECJ 和 JGAP 是两个最成熟的选项，也可能是最全面的选项。另一方面，它们的年龄意味着它们的目标是旧版本的 Java，这意味着没有泛型。
隐藏条款博客发表了一系列帖子（向下滚动列表查看它们）比较 JGAP、ECJ 和 Watchmaker。
在我没有编写的框架中， Jenes 可能是拥有我最喜欢的 API 的框架的样子。它也使用更现代的基于泛型的方法。
I wrote the Watchmaker Framework so my opinions are not unbiased. ECJ and JGAP are the two most established options and probably the most comprehensive. On the other hand their age means they target older versions of Java, which means no generics.
The Hidden Clause blog did a series of posts (scroll down the list to see them) comparing JGAP, ECJ and Watchmaker.
Of the frameworks I didn't write, Jenes is probably the one that has the API that I most like the look of. It too uses a more modern generics-based approach.
也许您会看看我写的 GA (Jenetics)。它使用 Javolution 库进行并行化，使用 JScience 库进行数字处理。我认为值得一看。
Maybe you will have a look at the GA (Jenetics) that I've written. It uses the Javolution library for parallelization and the JScience library for the numeric stuff. I think it's worth a look.
我知道 Apache Mahout（基于 Apache Hadoop）有大量机器学习类型算法 - 尽管不确定它是否正是您正在寻找的？
http://mahout.apache.org/
I know Apache Mahout (based on Apache Hadoop) has a load of machine learning type algorithms - although not sure if it's exactly what you're looking for?
http://mahout.apache.org/
这是我后来为自己的启发而添加的一个替代方案。我过去使用过 JGAP 并且对它很满意，但是这个似乎有很多优秀的例子，我想下次我需要优化代码时应该尝试一下。
http://watchmaker.uncommons.org/
This is an alternative I had bookmarked for my own edification later. I've used JGAP in the past and been happy with it, but this one seems to have lots of excellent examples and I thought I'd give it a try next time I needed optimization code.
http://watchmaker.uncommons.org/
我喜欢 Sean Luke 的 ECJ（Java 进化计算）：
http://cs.gmu.edu /~eclab/projects/ecj/
我还将此（独立）移植到了 C# .NET 4.0：
http ://branecloud.codeplex.com
本
I like Sean Luke's ECJ (Evolutionary Computation in Java):
http://cs.gmu.edu/~eclab/projects/ecj/
I've also ported this (independently) to C# .NET 4.0 here:
http://branecloud.codeplex.com
Ben
查看 Apache 数学 - 遗传学算法。我已经开始关注它了。由于我是遗传算法的新手，不确定这个库的全面性。它确实有一个很好的许可模型，可用于学术和商业用途（Apache 2.0）。
Check out Apache Math - Genetics Algorithm. I have started to look at it. As I'm new to Genetics Algorithms, not sure of the comprehensiveness or not of this library. It does have a nice licensing model for multiple uses for academic and commercial use (Apache 2.0).
看看 Java GALib，遗传算法库：
Have a look at Java GALib, Genetic Algorithm Library: