micom.duality¶
Implements a fast dual formulation.
Module Contents¶
Functions¶
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Add dual formulation to the problem. |
- micom.duality.fast_dual(model, prefix='dual_')[source]¶
Add dual formulation to the problem.
A mathematical optimization problem can be viewed as a primal and a dual problem. If the primal problem is a minimization problem the dual is a maximization problem, and the optimal value of the dual is a lower bound of the optimal value of the primal. For linear problems, strong duality holds, which means that the optimal values of the primal and dual are equal (duality gap = 0). This functions takes an optlang Model representing a primal linear problem and returns a new Model representing the dual optimization problem. The provided model must have a linear objective, linear constraints and only continuous variables. Furthermore, the problem must be in standard form, i.e. all variables should be non-negative. Both minimization and maximization problems are allowed.
- micom.duality.model¶
The model to be dualized.
- Type:
cobra.Model
- micom.duality.prefix¶
The string that will be prepended to all variable and constraint names in the returned dual problem.
- Type:
str
- Returns:
The coefficients for the new dual objective.
- Return type:
dict