如果需要性能，可以看看Grph。该图书馆由法国大学和CNRS/Inria开发。

http://www.i3s.unice.fr/~hogie/grph/

该项目是主动和被动的支持提供!

我不知道我是否可以称之为生产就绪，但是有jGABL。

JUNG是一个很好的可视化选择，并且也有一组相当不错的可用图算法，包括几种不同的随机图创建、重布线等机制。我还发现，在必要的地方扩展和调整它通常相当容易。

http://incubator.apache.org/hama/是Hadoop上用于大量矩阵和图形数据的分布式科学软件包。

If you were using JGraph, you should give a try to JGraphT which is designed for algorithms. One of its features is visualization using the JGraph library. It's still developed, but pretty stable. I analyzed the complexity of JGraphT algorithms some time ago. Some of them aren't the quickest, but if you're going to implement them on your own and need to display your graph, then it might be the best choice. I really liked using its API, when I quickly had to write an app that was working on graph and displaying it later.

相信一个图可以简单地表示为:

class Node {
   int value;
   List<Node> adj;
}

实现大部分你自己感兴趣的算法。如果您在一些关于图形的练习/学习过程中遇到了这个问题，那么这是最好的库。,)

对于大多数常见算法，你也可以选择邻接矩阵:

class SparseGraph {
  int[] nodeValues;
  List<Integer>[] edges;     
}

或者一些运算的矩阵:

class DenseGraph {
  int[] nodeValues;
  int[][] edges;     
}