Equality Constrained Composite-Step RSNK

class kona.algorithms.CompositeStepRSNK(primal_factory, state_factory, eq_factory, ineq_factory, optns={})

Bases: kona.algorithms.base_algorithm.OptimizationAlgorithm

A reduced-space composite-step optimization algorithm for PDE-governed equality constrained problems, globalized using a trust-region approach.

This implementation is based on the composite-step algorithm proposed by `Heinkenschloss and Ridzal<http://epubs.siam.org/doi/abs/10.1137/130921738>`_. However, we have omitted the inexactness corrections for simplicity and implemented a 2nd order adjoint approach for producing the necessary matrix-vector products.

Variables:

• factor_matrices (bool) – Boolean flag for matrix-based PDE solvers.
• min_radius, max_radius (radius,) – Trust radius parameters.
• mu_max, mu_pow (mu,) – Augmented Lagrangian constraint factor parameters.
• normal_KKT (AugmentedKKTMatrix) – Matrix object for the normal step system.
• tangent_KKT (LagrangianHessian) – Matrix object for the tangent step system.
• globalization (string) – Flag to determine solution globalization type.

backtracking_step()

calc_pred_reduction()

eval_merit(design, state, dual, cnstr)

solve()

trust_step()