如何将列表划分为较小的列表，以便一个元素遇到另一个元素的几率均匀分布？
我正在努力研究一种算法，将一组参赛者分成更小的组来进行轮次。以一组 20 人为例，我想将其分为 3 组（7,7,6）。比赛的每一轮，分组都是不同的，因此每个人都必须在相当公平的分配中与其他人竞争。
问题是，通过（天真的）随机选择，一个人必须比另一个人更多地与同一个人战斗。即两个元素通常最终位于同一组中。
我想让这更加公平，以便对于给定数量的参赛者、组大小（并非所有组的大小都相同）和轮数，算法会在每轮中找到一组公平的组，以便平均每个参赛者都有在各轮比赛中遇到同一参赛者的几率相同。
有没有关于这个主题的文献可供参考？或者任何已知的算法？
I'm struggling with an algorithm to divide a group of contestants into smaller groups to make up rounds. Take for example a group of 20 people, which I want to divide into 3 groups (7,7,6). For each round in a contest, the groups are different, so that everybody has to combat everybody else in a rather fair distribution.
The problem is that with a (naive) random selection one person has to combat the same person more then another one. I.e. Two elements end up often in the same group.
I would like to make this more fair so that for a given number of contestants, group size (not all groups are the same size) and number of rounds, the algorithm finds a fair set of groups per round so that on average every contestant has the same odds of meeting the same contestant during the rounds.
Is there any literature on this topic I can consult? Or any known algorithms?
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您正在进入一个已在组合学中探索过的主题，但实际上生成这些设计却非常棘手。有关此类示例，请参阅 http://en.wikipedia.org/wiki/Block_design您想要了解更多的事情。如果您需要帮助，我建议您在 https://math.stackexchange.com/ 上提问，因为您更有可能找到人谁还记得这个东西。 （我在这个世纪还没有必要看这些东西，否则我会说一些更有用的东西。）
You're getting into a topic that has been explored in combinatorics, but actually producing those designs is surprisingly tricky. See http://en.wikipedia.org/wiki/Block_design for a sample of the sorts of things you'll want to learn more about. If you need help, I suggest asking on https://math.stackexchange.com/ because you'll be more likely to find someone who remembers this stuff. (I haven't had to look at this stuff in this millenium, or else I'd say something more useful about it.)
你可以看看这个方法：random.sample(population, k)
you can have a look to this method : random.sample(population, k)