For example, consider a \(11 \times 11\) grid, and choose from the following building blocks:

Five different polyominos |

Fail to cover complete grid |

\[x_{i,j,k} = \begin{cases} 1 & \text{if we place polyomino $k$ at location $(i,j)$}\\ 0 & \text{otherwise} \end{cases}\]

I used as rule that the left-upper corner of each polynomino is its anchor. I.e. in the picture above we have \(x_{1,1,4} = 1\), \(x_{2,1,2}=1\), \(x_{1,3,5}=1\) etc.

To formulate a non-overlap constraint I populated a set \(cover_{i,j,k,i',j'}\), with elements that exist if cell \((i',j')\) is covered when we place polyomino \(k\) in cell \((i,j)\). To require each cell \((i',j')\) is covered we can say:

\[ \forall i',j': \sum_{i,j,k|cover_{i,j,k,i',j'}} x_{i,j,k} = 1\]

This constraint is infeasible if we cannot cover each cell \((i',j')\) exactly once. In order to make sure we can show a meaningful solution when we cannot cover each cell, we formulate the following optimization model:

\[\begin{align} \max\>&\sum_{i,j} y_{i,j}\\&y_{i',j'} = \sum_{i,j,k|cover_{i,j,k,i',j'}} x_{i,j,k}\\&x_{i,j,k}\in \{0,1\}\\&y_{i,j} \in \{0,1\}\end{align}\]

Here \(y_{i,j}=1\) indicates cell \((i,j)\) is covered exactly once, and \(y_{i,j}=0\) says the cell is not covered.

With a little bit of effort we can produce the following:

61 x 61 board with 9 different polyominos |

#### References

- Polyomino, https://en.wikipedia.org/wiki/Polyomino
- 2D bin packing on a grid, https://stackoverflow.com/questions/47918792/2d-bin-packing-on-a-grid