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SMDM-heuristics

Heuristics for Signed Modularity Density Maximization 🎓

To apply the heuristics run:

python3 main.py id lbda m dataset/file.net r -d

Where:

✨ id is the identifier of the execution (string)

✨ lbda is the lambda value (float)

✨ m is the quantity of solutions to be created (int)

✨ dataset/file.net is the data file (.net)

✨ r is the quantity executions for the same config (int)

✨ -v is an optional argument to enter VERBOSE mode

✨ -d is an optional argument to enter DEBUG mode

✨ -l is an optional argument to enter Debug Local Search mode

✨ -f is an optional argument to enter Debug Find Solutions mode

✨ -lo is an optional argument to run and debug only Local Search

✨ -fo is an optional argument to run and debug only Find Solutions

✨ -p is an optional argument to run on parallel mode

Example:

python3 main.py graph 0.5 10 dataset/gahuku.net 30

The result of the execution is a graph clustering solution and its density, aiming to analyze and compare it with other computational methods present in the literature.

To get the results, a GRASP-based heuristic was developed and applied.