极值竞技场
中/EN
P01 · 装箱与覆盖 · 经典问题 · 难

单位正方形内的等圆装箱 · n = 99

文献中也称circle packing in a squarepacking equal circles in a unit squarecsq

在边长 1 的正方形内放置 n 个半径相同、互不重叠的圆，使共同半径尽可能大。

子题n = 99
目标最大化 共同半径

纪录对比

共同半径 · 越大越好
纪录数值 / 区间作者 / 持有人来源
外部已知最好[0.0519786064495, 0.0519786064505]见来源署名packomania.com ↗
本站纪录暂无选手纪录——

严格定义

  • 容器单位正方形：左下角是原点 (0, 0)，右上角是 (1, 1)
  • 提交恰好 n 个圆：一个共同半径 radius 与 n 个圆心 centers
  • 约束每个圆完整落在容器内；两两内部不重叠，相切允许
  • 目标让共同半径尽可能大
放大来摆，然后提交 ↗

当前展示：起步布局

1y0
0x1
已验证构造r = 0.051978606

帮助理解

哪里有优化空间

最优构形是「卡死」的接触结构：圆彼此顶住、顶住边界，常出现斜排、错位、以及不碰任何邻居的游离圆。规整的网格摆法几乎从不最优。

前沿在哪里

n = 1–30 已证明最优，适合观察经典接触结构；n = 31–300 接入 Packomania 的公开前沿，除 n = 36 外最优性仍未知。大规模部分集中成一张表，供算法批量挑战。

查看来源
单位正方形内的等圆装箱 n = 99 的当前构型
构型与历史

起步布局

查看构型、求解笔记与纪录历史。

挑战这个纪录 ↗提交证明 / 思路 ↓在讨论区分享证明或思路，审核采纳后可获得证明分。
ANSWER FORMAT

答案怎么写

容器是边长 1 的正方形，左下角是原点 (0, 0)，右上角是 (1, 1)。坐标和长度用同一个单位，直接写成小数，例如 "0.5"，最多九位小数。

提交 radius 与 centers。每个数写成十进制字符串，例如 "0.25"。

起步布局答案

{
  "centers": [
    [
      "0.051978606",
      "0.051978606"
    ],
    [
      "0.231187164",
      "0.051978606"
    ],
    [
      "0.410395721",
      "0.051978606"
    ],
    [
      "0.589604279",
      "0.051978606"
    ],
    [
      "0.768812836",
      "0.051978606"
    ],
    [
      "0.948021394",
      "0.051978606"
    ],
    [
      "0.141582885",
      "0.104687006"
    ],
    [
      "0.320791443",
      "0.104687006"
    ],
    [
      "0.5",
      "0.104687006"
    ],
    [
      "0.679208557",
      "0.104687006"
    ],
    [
      "0.858417115",
      "0.104687006"
    ],
    [
      "0.051978606",
      "0.157395405"
    ],
    [
      "0.231187164",
      "0.157395405"
    ],
    [
      "0.410395721",
      "0.157395405"
    ],
    [
      "0.589604279",
      "0.157395405"
    ],
    [
      "0.768812836",
      "0.157395405"
    ],
    [
      "0.948021394",
      "0.157395405"
    ],
    [
      "0.141582885",
      "0.210103804"
    ],
    [
      "0.320791443",
      "0.210103804"
    ],
    [
      "0.5",
      "0.210103804"
    ],
    [
      "0.679208557",
      "0.210103804"
    ],
    [
      "0.858417115",
      "0.210103804"
    ],
    [
      "0.051978606",
      "0.262812203"
    ],
    [
      "0.231187164",
      "0.262812203"
    ],
    [
      "0.410395721",
      "0.262812203"
    ],
    [
      "0.589604279",
      "0.262812203"
    ],
    [
      "0.768812836",
      "0.262812203"
    ],
    [
      "0.948021394",
      "0.262812203"
    ],
    [
      "0.141582885",
      "0.315520603"
    ],
    [
      "0.320791443",
      "0.315520603"
    ],
    [
      "0.5",
      "0.315520603"
    ],
    [
      "0.679208557",
      "0.315520603"
    ],
    [
      "0.858417115",
      "0.315520603"
    ],
    [
      "0.051978606",
      "0.368229002"
    ],
    [
      "0.231187164",
      "0.368229002"
    ],
    [
      "0.410395721",
      "0.368229002"
    ],
    [
      "0.589604279",
      "0.368229002"
    ],
    [
      "0.768812836",
      "0.368229002"
    ],
    [
      "0.948021394",
      "0.368229002"
    ],
    [
      "0.141582885",
      "0.420937401"
    ],
    [
      "0.320791443",
      "0.420937401"
    ],
    [
      "0.5",
      "0.420937401"
    ],
    [
      "0.679208557",
      "0.420937401"
    ],
    [
      "0.858417115",
      "0.420937401"
    ],
    [
      "0.051978606",
      "0.4736458"
    ],
    [
      "0.231187164",
      "0.4736458"
    ],
    [
      "0.410395721",
      "0.4736458"
    ],
    [
      "0.589604279",
      "0.4736458"
    ],
    [
      "0.768812836",
      "0.4736458"
    ],
    [
      "0.948021394",
      "0.4736458"
    ],
    [
      "0.141582885",
      "0.5263542"
    ],
    [
      "0.320791443",
      "0.5263542"
    ],
    [
      "0.5",
      "0.5263542"
    ],
    [
      "0.679208557",
      "0.5263542"
    ],
    [
      "0.858417115",
      "0.5263542"
    ],
    [
      "0.051978606",
      "0.579062599"
    ],
    [
      "0.231187164",
      "0.579062599"
    ],
    [
      "0.410395721",
      "0.579062599"
    ],
    [
      "0.589604279",
      "0.579062599"
    ],
    [
      "0.768812836",
      "0.579062599"
    ],
    [
      "0.948021394",
      "0.579062599"
    ],
    [
      "0.141582885",
      "0.631770998"
    ],
    [
      "0.320791443",
      "0.631770998"
    ],
    [
      "0.5",
      "0.631770998"
    ],
    [
      "0.679208557",
      "0.631770998"
    ],
    [
      "0.858417115",
      "0.631770998"
    ],
    [
      "0.051978606",
      "0.684479397"
    ],
    [
      "0.231187164",
      "0.684479397"
    ],
    [
      "0.410395721",
      "0.684479397"
    ],
    [
      "0.589604279",
      "0.684479397"
    ],
    [
      "0.768812836",
      "0.684479397"
    ],
    [
      "0.948021394",
      "0.684479397"
    ],
    [
      "0.141582885",
      "0.737187797"
    ],
    [
      "0.320791443",
      "0.737187797"
    ],
    [
      "0.5",
      "0.737187797"
    ],
    [
      "0.679208557",
      "0.737187797"
    ],
    [
      "0.858417115",
      "0.737187797"
    ],
    [
      "0.051978606",
      "0.789896196"
    ],
    [
      "0.231187164",
      "0.789896196"
    ],
    [
      "0.410395721",
      "0.789896196"
    ],
    [
      "0.589604279",
      "0.789896196"
    ],
    [
      "0.768812836",
      "0.789896196"
    ],
    [
      "0.948021394",
      "0.789896196"
    ],
    [
      "0.141582885",
      "0.842604595"
    ],
    [
      "0.320791443",
      "0.842604595"
    ],
    [
      "0.5",
      "0.842604595"
    ],
    [
      "0.679208557",
      "0.842604595"
    ],
    [
      "0.858417115",
      "0.842604595"
    ],
    [
      "0.051978606",
      "0.895312994"
    ],
    [
      "0.231187164",
      "0.895312994"
    ],
    [
      "0.410395721",
      "0.895312994"
    ],
    [
      "0.589604279",
      "0.895312994"
    ],
    [
      "0.768812836",
      "0.895312994"
    ],
    [
      "0.948021394",
      "0.895312994"
    ],
    [
      "0.141582885",
      "0.948021394"
    ],
    [
      "0.320791443",
      "0.948021394"
    ],
    [
      "0.5",
      "0.948021394"
    ],
    [
      "0.679208557",
      "0.948021394"
    ],
    [
      "0.858417115",
      "0.948021394"
    ]
  ],
  "radius": "0.051978606"
}
提交格式与技术细节需要编写程序或准备 JSON 答案时再查看＋

子题参数

{
  "n": 99
}

起步布局答案

{
  "centers": [
    [
      "0.051978606",
      "0.051978606"
    ],
    [
      "0.231187164",
      "0.051978606"
    ],
    [
      "0.410395721",
      "0.051978606"
    ],
    [
      "0.589604279",
      "0.051978606"
    ],
    [
      "0.768812836",
      "0.051978606"
    ],
    [
      "0.948021394",
      "0.051978606"
    ],
    [
      "0.141582885",
      "0.104687006"
    ],
    [
      "0.320791443",
      "0.104687006"
    ],
    [
      "0.5",
      "0.104687006"
    ],
    [
      "0.679208557",
      "0.104687006"
    ],
    [
      "0.858417115",
      "0.104687006"
    ],
    [
      "0.051978606",
      "0.157395405"
    ],
    [
      "0.231187164",
      "0.157395405"
    ],
    [
      "0.410395721",
      "0.157395405"
    ],
    [
      "0.589604279",
      "0.157395405"
    ],
    [
      "0.768812836",
      "0.157395405"
    ],
    [
      "0.948021394",
      "0.157395405"
    ],
    [
      "0.141582885",
      "0.210103804"
    ],
    [
      "0.320791443",
      "0.210103804"
    ],
    [
      "0.5",
      "0.210103804"
    ],
    [
      "0.679208557",
      "0.210103804"
    ],
    [
      "0.858417115",
      "0.210103804"
    ],
    [
      "0.051978606",
      "0.262812203"
    ],
    [
      "0.231187164",
      "0.262812203"
    ],
    [
      "0.410395721",
      "0.262812203"
    ],
    [
      "0.589604279",
      "0.262812203"
    ],
    [
      "0.768812836",
      "0.262812203"
    ],
    [
      "0.948021394",
      "0.262812203"
    ],
    [
      "0.141582885",
      "0.315520603"
    ],
    [
      "0.320791443",
      "0.315520603"
    ],
    [
      "0.5",
      "0.315520603"
    ],
    [
      "0.679208557",
      "0.315520603"
    ],
    [
      "0.858417115",
      "0.315520603"
    ],
    [
      "0.051978606",
      "0.368229002"
    ],
    [
      "0.231187164",
      "0.368229002"
    ],
    [
      "0.410395721",
      "0.368229002"
    ],
    [
      "0.589604279",
      "0.368229002"
    ],
    [
      "0.768812836",
      "0.368229002"
    ],
    [
      "0.948021394",
      "0.368229002"
    ],
    [
      "0.141582885",
      "0.420937401"
    ],
    [
      "0.320791443",
      "0.420937401"
    ],
    [
      "0.5",
      "0.420937401"
    ],
    [
      "0.679208557",
      "0.420937401"
    ],
    [
      "0.858417115",
      "0.420937401"
    ],
    [
      "0.051978606",
      "0.4736458"
    ],
    [
      "0.231187164",
      "0.4736458"
    ],
    [
      "0.410395721",
      "0.4736458"
    ],
    [
      "0.589604279",
      "0.4736458"
    ],
    [
      "0.768812836",
      "0.4736458"
    ],
    [
      "0.948021394",
      "0.4736458"
    ],
    [
      "0.141582885",
      "0.5263542"
    ],
    [
      "0.320791443",
      "0.5263542"
    ],
    [
      "0.5",
      "0.5263542"
    ],
    [
      "0.679208557",
      "0.5263542"
    ],
    [
      "0.858417115",
      "0.5263542"
    ],
    [
      "0.051978606",
      "0.579062599"
    ],
    [
      "0.231187164",
      "0.579062599"
    ],
    [
      "0.410395721",
      "0.579062599"
    ],
    [
      "0.589604279",
      "0.579062599"
    ],
    [
      "0.768812836",
      "0.579062599"
    ],
    [
      "0.948021394",
      "0.579062599"
    ],
    [
      "0.141582885",
      "0.631770998"
    ],
    [
      "0.320791443",
      "0.631770998"
    ],
    [
      "0.5",
      "0.631770998"
    ],
    [
      "0.679208557",
      "0.631770998"
    ],
    [
      "0.858417115",
      "0.631770998"
    ],
    [
      "0.051978606",
      "0.684479397"
    ],
    [
      "0.231187164",
      "0.684479397"
    ],
    [
      "0.410395721",
      "0.684479397"
    ],
    [
      "0.589604279",
      "0.684479397"
    ],
    [
      "0.768812836",
      "0.684479397"
    ],
    [
      "0.948021394",
      "0.684479397"
    ],
    [
      "0.141582885",
      "0.737187797"
    ],
    [
      "0.320791443",
      "0.737187797"
    ],
    [
      "0.5",
      "0.737187797"
    ],
    [
      "0.679208557",
      "0.737187797"
    ],
    [
      "0.858417115",
      "0.737187797"
    ],
    [
      "0.051978606",
      "0.789896196"
    ],
    [
      "0.231187164",
      "0.789896196"
    ],
    [
      "0.410395721",
      "0.789896196"
    ],
    [
      "0.589604279",
      "0.789896196"
    ],
    [
      "0.768812836",
      "0.789896196"
    ],
    [
      "0.948021394",
      "0.789896196"
    ],
    [
      "0.141582885",
      "0.842604595"
    ],
    [
      "0.320791443",
      "0.842604595"
    ],
    [
      "0.5",
      "0.842604595"
    ],
    [
      "0.679208557",
      "0.842604595"
    ],
    [
      "0.858417115",
      "0.842604595"
    ],
    [
      "0.051978606",
      "0.895312994"
    ],
    [
      "0.231187164",
      "0.895312994"
    ],
    [
      "0.410395721",
      "0.895312994"
    ],
    [
      "0.589604279",
      "0.895312994"
    ],
    [
      "0.768812836",
      "0.895312994"
    ],
    [
      "0.948021394",
      "0.895312994"
    ],
    [
      "0.141582885",
      "0.948021394"
    ],
    [
      "0.320791443",
      "0.948021394"
    ],
    [
      "0.5",
      "0.948021394"
    ],
    [
      "0.679208557",
      "0.948021394"
    ],
    [
      "0.858417115",
      "0.948021394"
    ]
  ],
  "radius": "0.051978606"
}

提交 radius 与 centers。每个数写成十进制字符串，例如 "0.25"。 · 验证器 v1.0.0

DISCUSSION

讨论区

聊思路、贴方法、问为什么卡住。所有登录用户都可以发帖；发言公开署名，与纪录使用同一个名字，署名后的 #编号是账号注册序号，冒不了名。新发言经自动审核后公开。

啊？？！NUE_13#310 条回复空悲切/.lird#282 条回复