PROBLEM CATALOG

40 verifiable
mathematical arenas.

DRAGGABLE
P01Packing and covering
  • Solved
  • Classic

Equal-circle packing in a unit square

Place n equal circles and maximize their common radius.

Instance
n = 1–30
Objective
Maximize common radius
Progress
30 of 30 finished
DRAGGABLE
P02Packing and covering
  • Classic
  • Weak baseline

Equal-circle packing in a unit circle

Place n non-overlapping equal circles inside the unit circle.

Instance
n = 1–29
Objective
Maximize common radius
Progress
14 of 29 finished
DRAGGABLE
P03Extremal configurations
  • Classic

Heilbronn minimum triangle area

Place n points and maximize the smallest triangle area among all triples.

Instance
n = 1–12
Objective
Maximize minimum triangle area
Progress
0 of 12 finished
DRAGGABLE
P04Packing and covering
  • Classic

Common-scale consecutive rectangle packing

Pack scaled copies of 1×1, 1×2, …, 1×n into the unit square.

Instance
n = 1–20
Objective
Maximize common scale
Progress
2 of 20 finished
DRAGGABLE
P05Packing and covering
  • Classic

Tilted equal squares in a circle

Place n equal squares inside a circle of radius 1, each free to tilt, and maximize their common side.

Instance
n = 1–12
Objective
Maximize the smallest side
Progress
1 of 12 finished
DRAGGABLE
P06Packing and covering
  • Classic

Packing circles of radius 1,2,…,n into a circle

Pack n mutually non-overlapping circles of radii 1,2,…,n, drawn to scale, into a circle and minimize its radius.

Instance
n = 1–29
Objective
Minimize container radius
Progress
3 of 29 finished
DRAGGABLE
P07Extremal configurations
  • Classic

Spreading points in a circle

Place n points inside a circle of radius 1 so that the smallest distance between any two is as large as possible.

Instance
n = 1–17
Objective
Maximize the smallest distance between two points
Progress
1 of 17 finished
DRAGGABLE
P08Packing and covering
  • Formed here

Equal circles in an L

Place n equal circles inside an L-shaped region, making their common radius as large as possible.

Instance
n = 1–15
Objective
Maximize common radius
Progress
0 of 15 finished
DRAGGABLE
P09Packing and covering
  • Classic

Equal circles in a half-disc

Place n equal circles in a half-disc of radius 1, making their common radius as large as possible.

Instance
n = 1–14
Objective
Maximize common radius
Progress
0 of 14 finished
DRAGGABLE
P10Packing and covering
  • Formed here

Equal circles in a plus sign

Place n equal circles inside a plus-shaped region, making their common radius as large as possible.

Instance
n = 1–16
Objective
Maximize common radius
Progress
0 of 16 finished
DRAGGABLE
P11Packing and covering
  • Classic

Equal-circle packing in a right triangle

Place n non-overlapping equal circles inside a fixed right triangle with legs 1 and 0.75, maximizing their common radius.

Instance
n = 1–11
Objective
Maximize common radius
Progress
0 of 11 finished
DRAGGABLE
P12Packing and covering
  • Classic

Equal-circle packing in a 2:1 rectangle

Place n non-overlapping equal circles in a 2×1 rectangle, maximizing their common radius.

Instance
n = 1–10
Objective
Maximize common radius
Progress
4 of 10 finished
DRAGGABLE
P13Packing and covering
  • Classic

Packing circles of radius 1,2,…,n into a square

Pack n mutually non-overlapping circles of radii 1,2,…,n, drawn to scale, into a square and minimize its side.

Instance
n = 1–29
Objective
Minimize square side
Progress
3 of 29 finished
DRAGGABLE
P15Packing and covering
  • Classic

Spreading points in the unit square

Place n points in the unit square so that the smallest distance between any two of them is as large as possible.

Instance
n = 1–11
Objective
Maximize the smallest distance between two points
Progress
4 of 11 finished
DRAGGABLE
P16Extremal configurations
  • Formed here

Spreading points in a right triangle

Place n points in a right isosceles triangle with legs 1, maximizing the smallest distance between any two.

Instance
n = 1–15
Objective
Maximize the smallest distance between two points
Progress
0 of 15 finished
DRAGGABLE
P17Extremal configurations
  • Formed here

Spreading points in a rectangle

Place n points in a 2 × 1 rectangle, maximizing the smallest distance between any two.

Instance
n = 1–17
Objective
Maximize the smallest distance between two points
Progress
0 of 17 finished
DRAGGABLE
P18Packing and covering
  • Classic
  • Weak baseline

Tilted equal squares in the unit square

Place n equal squares inside the unit square, each free to tilt, and maximize their common side.

Instance
n = 1–28
Objective
Maximize the smallest side
Progress
10 of 28 finished
DRAGGABLE
P19Extremal configurations
  • Formed here

Spreading points in an L

Place n points in an L-shaped region, maximizing the smallest distance between any two.

Instance
n = 1–17
Objective
Maximize the smallest distance between two points
Progress
0 of 17 finished
DRAGGABLE
P20Extremal configurations
  • Formed here

Spreading points in a half-disc

Place n points in a half-disc of radius 1, maximizing the smallest distance between any two.

Instance
n = 1–15
Objective
Maximize the smallest distance between two points
Progress
0 of 15 finished
DRAGGABLE
P21Extremal configurations
  • Formed here

Spreading points in a plus sign

Place n points in a plus-shaped region, maximizing the smallest distance between any two.

Instance
n = 1–17
Objective
Maximize the smallest distance between two points
Progress
0 of 17 finished
DRAGGABLE
P22Extremal configurations
  • Classic

The smallest triangle in a disc

Place n points in a disc of radius 1 so the smallest triangle any three of them make is as large as possible.

Instance
n = 1–10
Objective
Maximize the smallest triangle's area
Progress
0 of 10 finished
DRAGGABLE
P24Extremal configurations
  • Formed here

The smallest triangle in an L

Place n points in an L-shaped region so the smallest triangle any three of them make is as large as possible.

Instance
n = 1–10
Objective
Maximize the smallest triangle's area
Progress
0 of 10 finished
DRAGGABLE
P25Extremal configurations
  • Formed here

The smallest triangle in a plus sign

Place n points in a plus-shaped region so the smallest triangle any three of them make is as large as possible.

Instance
n = 1–10
Objective
Maximize the smallest triangle's area
Progress
0 of 10 finished
DRAGGABLE
P26Extremal configurations
  • Formed here

The smallest triangle in a half-disc

Place n points in a half-disc of radius 1 so the smallest triangle any three of them make is as large as possible.

Instance
n = 1–10
Objective
Maximize the smallest triangle's area
Progress
0 of 10 finished
DRAGGABLE
P27Extremal configurations
  • Formed here

Spreading points in an annulus

Place n points in an annulus of outer radius 1 and inner radius 0.5, maximizing the smallest distance between any two.

Instance
n = 1–17
Objective
Maximize the smallest distance between two points
Progress
1 of 17 finished
DRAGGABLE
P28Extremal configurations
  • Formed here

The smallest triangle in an annulus

Place n points in an annulus of outer radius 1 and inner radius 0.5 so the smallest triangle any three of them make is as large as possible.

Instance
n = 1–10
Objective
Maximize the smallest triangle's area
Progress
0 of 10 finished
DRAGGABLE
P29Extremal configurations
  • Classic

Heilbronn's problem in a triangle

Place n points inside the right triangle (0,0), (size,0), (0,size) and maximize the smallest triangle area among all triples.

Instance
n = 1–6
Objective
Maximize the smallest triangle's area
Progress
3 of 6 finished
DRAGGABLE
P30Packing and covering
  • Classic

Equal circles in a quadrant

Place n equal circles in a quarter-disc of radius 1, making their common radius as large as possible.

Instance
n = 1–14
Objective
Maximize common radius
Progress
0 of 14 finished
DRAGGABLE
P31Extremal configurations
  • Formed here

Spreading points in a quadrant

Place n points in a quarter-disc of radius 1, maximizing the smallest distance between any two.

Instance
n = 1–15
Objective
Maximize the smallest distance between two points
Progress
0 of 15 finished
DRAGGABLE
P32Extremal configurations
  • Formed here

The smallest triangle in a quadrant

Place n points in a quarter-disc of radius 1 so the smallest triangle any three of them make is as large as possible.

Instance
n = 1–10
Objective
Maximize the smallest triangle's area
Progress
0 of 10 finished
DRAGGABLE
P33Extremal configurations
  • Classic
  • Weak baseline

Riesz 2-energy in a square

Place n points in the unit square, minimizing the sum of 1/distance² over every pair.

Instance
n = 1–20
Objective
Minimize Riesz 2-energy
Progress
0 of 20 finished
DRAGGABLE
P34Extremal configurations
  • Classic
  • Weak baseline

Riesz 2-energy in a disc

Place n points in a disc of radius 1, minimizing the sum of 1/distance² over every pair.

Instance
n = 1–20
Objective
Minimize Riesz 2-energy
Progress
0 of 20 finished
DRAGGABLE
P51Extremal configurations
  • Classic

Lighting a unit square

Place n lights of unit brightness in a unit square so the darkest point of the square is as bright as possible.

Instance
n = 1–19
Objective
Maximize minimum intensity
Progress
0 of 19 finished
DRAGGABLE
P52Extremal configurations
  • Classic

Smallest ratio of largest to smallest distance

Place n points so the distance between the furthest pair, divided by the distance between the closest pair, is as small as possible.

Instance
n = 1–20
Objective
Minimize max-to-min distance ratio
Progress
0 of 20 finished
DRAGGABLE
P53Extremal configurations
  • Classic
  • Applied frontier
  • Weak baseline

The biggest little polygon

Take n points with no two further than 1 apart, and make the convex polygon they enclose as large as possible.

Instance
n = 1–13
Objective
Maximize the area
Progress
4 of 13 finished
DRAGGABLE
P54Extremal configurations
  • Classic
  • Applied frontier
  • Weak baseline

Minimum star discrepancy in the unit square

You have n samples to spread over a square frame. Any rectangle measured from one corner should hold the same share of the samples as it holds of the area; the worst mismatch is your score.

Instance
n = 1–29
Objective
Minimize the worst gap D*
Progress
0 of 29 finished
DRAGGABLE
P55Extremal configurations
  • Classic
  • Applied frontier
  • Weak baseline

Optimal quantization in the unit square

Place n respawn points on a square map. A player appears uniformly at random and is sent to the nearest one; make the average squared trip as short as you can.

Instance
n = 1–25
Objective
Minimize the average squared distance
Progress
0 of 25 finished
DRAGGABLE
P56Extremal configurations
  • Formed here
  • Applied frontier
  • Weak baseline

The most uniform sampling mesh in the unit square

Place n points in the unit square; the red circle is the largest uncovered hole and the blue line the closest pair. Make the ratio of hole radius to pair spacing as small as you can.

Instance
n = 1–36
Objective
Minimize the uniformity M
Progress
0 of 36 finished
DRAGGABLE
P57Packing and covering
  • Classic
  • Weak baseline

Sum of radii in the unit square

Place n non-overlapping circles of any sizes in the unit square, maximizing the sum of their radii.

Instance
n = 1–30
Objective
Maximize sum of the radii
Progress
1 of 30 finished
DRAGGABLE
P58Extremal configurations
  • Classic

The smallest triangle in an equilateral triangle

Place n points in an equilateral triangle of side 1 so the smallest triangle any three of them make is as large as possible.

Instance
n = 1–10
Objective
Maximize the smallest triangle's area
Progress
0 of 10 finished