Two strategies to decompose optimization problems are proposed.

The first strategy identifies clusters of connected variables.

The second strategy finds the optimal partition given a set number of sub-problems.

The strategies find optimal partitions in the test cases presented.

The strategies presented can also be used for model-based decomposition.