isse-augsburg/minibrass
Modeling preferences and soft constraints -- qualitatively and quantitatively on top of MiniZinc
MiniBrass helps operations researchers, scheduling managers, and planners define and solve complex problems where not all constraints are equally strict. It allows you to feed in a problem description with both 'must-have' rules and 'nice-to-have' preferences, then outputs the best possible solution that balances these different priorities. This is useful for anyone designing systems or schedules that need to be optimized for multiple, sometimes conflicting, objectives.
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Use this if you need to find an optimal solution to a problem with many variables, where some rules are absolute requirements and others are flexible preferences or wishes.
Not ideal if your problem only involves strict, absolute constraints with no need to express or prioritize 'soft' preferences.
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Language
Jupyter Notebook
License
MIT
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Last pushed
May 23, 2023
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