Symbolic & Numeric Calculus

Find the Largest Small Polygon

Find the polygon with maximal area among polygons with sides and diameter .

In Mathematica 11, FindMinimum adds an IPOPT solver to solve large-scale constrained optimization problems more efficiently.

Denote by n the number of vertices of the polygon.

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n = 50;

Let be the polar coordinates of the ^(th) vertex of the polygon.

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vars = Join[Array[r, n], Array[\[Theta], n]];

They satisfy the constraints , , , .

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varbounds = Join[Table[0 <= r[i] <= 1, {i, n - 1}], {r[n] == 0}, Table[0 <= \[Theta][i] <= Pi, {i, n - 1}], {\[Theta][n] == Pi}];

The area of the polygon is the sum of the areas of triangles with vertices , , and (the origin).

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area = 1/2 Sum[ r[i] r[i + 1] Sin[\[Theta][i + 1] - \[Theta][i]], {i, 1, n - 1}];

The distance between every two vertices should not exceed 1.

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constr1 = Flatten[Table[ 0 < r[i]^2 + r[j]^2 - 2 r[i] r[j] Cos[\[Theta][i] - \[Theta][j]] <= 1, {i, 1, n - 1}, {j, i + 1, n}], 2];

Due to the vertex ordering, the following constraints also exist.

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constr2 = Table[\[Theta][i] <= \[Theta][i + 1], {i, 1, n - 1}];

Choose initial points for the variables.

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x0 = vars /. {r[i_] -> 4. i (n + 1 - i)/(n + 1)^2, \[Theta][i_] -> \[Pi] i/n};

Maximize the area subject to the constraints.

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sol = FindMaximum[{area, constr1, constr2, varbounds}, Thread[{vars, x0}]];

Convert to Cartesian coordinates.

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rectpts = Table[FromPolarCoordinates[{r[i], \[Theta][i]}], {i, 1, n}] /. sol[[2]];

Plot the solution.

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Show[ListPlot[rectpts, PlotStyle -> {Blue, PointSize -> Medium}], Graphics[{Opacity[.1], Blue, EdgeForm[Blue], Polygon[rectpts]}], AspectRatio -> 1, ImageSize -> Medium]
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