object AugLagrangian
The AugLagrangian class implements the Augmented Lagrangian Method for
solving equality constrained optimization problems.
Minimize objective function 'f' subject to constraint 'h' to find an optimal
solution for 'x'.
min f(x) s.t. h(x) = 0
f = objective function h = equality contraint x = solution vector
Note: the hyper-parameters 'eta' and 'p0' will need to be tuned per problem.
- See also
AugLagrangianTestfor how to set up 'f', 'h' and 'grad' functions
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- type Gradient = (VectoD, Double, Double) => VectoD
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- def solve(x: VectoD, f: FunctionV_2S, h: FunctionV_2S, grad: Gradient): (VectoD, MatriD)
Solve for an optimal solution to the equality constrained optimization problem.
Solve for an optimal solution to the equality constrained optimization problem.
- x
initial guess for solution vector
- f
the objective function to be minimized
- h
the equality constraint
- grad
the gradient of Lagranian (must be specified by caller)
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