bundles / scipy latest / scipy / optimize / _trustregion_constr / equality_constrained_sqp / equality_constrained_sqp
function
scipy.optimize._trustregion_constr.equality_constrained_sqp:equality_constrained_sqp
Signature
def equality_constrained_sqp(fun_and_constr, grad_and_jac, lagr_hess, x0, fun0, grad0, constr0, jac0, stop_criteria, state, initial_penalty, initial_trust_radius, factorization_method, trust_lb = None, trust_ub = None, scaling = <function default_scaling at 0x0000>)Summary
Solve nonlinear equality-constrained problem using trust-region SQP.
Extended Summary
Solve optimization problem:
minimize fun(x) subject to: constr(x) = 0
using Byrd-Omojokun Trust-Region SQP method described in [1]. Several implementation details are based on [2] and [3], p. 549.
Aliases
scipy.optimize._trustregion_constr.equality_constrained_sqp.equality_constrained_sqp