AIMMS to IPOPT Mapping

Description

The table shows in the left column the AIMMS IPOPT options while the right column displays the associated IPOPT parameter.

Option name in AIMMS

Name in IPOPT

Adaptive strategy factor limit

mu_max_fact

Adaptive strategy oracle

mu_oracle

Barrier convergence tolerance factor

barrier_tol_factor

Barrier parameter initial value

mu_init

Barrier parameter update strategy

mu_strategy

Execute Mehrotra algorithm

mehrotra_algorithm

Fixed mode oracle

fixed_mu_oracle

Linear decrease factor barrier parameter

mu_linear_decrease_factor

Maximum value for barrier parameter

mu_max

Minimum value for barrier parameter

mu_min

Quality function section steps limit

quality_function_max_section_steps

Superlinear decrease rate barrier parameter

mu_superlinear_decrease_power

Derivative checker verbosity

derivative_test_print_all

Derivative test perturbation size

derivative_test_perturbation

Derivative test tolerance

derivative_test_tol

Derivative testing

derivative_test

Maximum perturbation of evaluation point

point_perturbation_radius

First Hessian perturbation increase factor

perturb_inc_fact_first

First Hessian perturbation size

first_hessian_perturbation

Hessian perturbation decrease factor

perturb_dec_fact

Hessian perturbation increase factor

perturb_inc_fact

Jacobian regularization value

jacobian_regularization_value

Maximum Hessian perturbation

max_hessian_perturbation

Minimum Hessian perturbation

min_hessian_perturbation

Bound multipliers initialization method

bound_mult_init_method

Constraint multipliers initial guess limit

constr_mult_init_max

Initial value for bound multipliers

bound_mult_init_val

Point to bound absolute distance

bound_push

Point to bound relative distance

bound_frac

Slack to bound absolute distance

slack_bound_push

Slack to bound relative distance

slack_bound_frac

Always accept full trial step

accept_every_trial_step

Corrector steps type

corrector_type

Maximum number of watchdog iterations

watchdog_trial_iter_max

Second order correction trial steps limit

max_soc

Watchdog shortened iteration trigger

watchdog_shortened_iter_trigger

Linear solver selection

linear_solver

Linear system scaling

linear_scaling_on_demand

Linear system scaling method

linear_system_scaling

MA27 increment factor for workspace size

ma27_meminc_factor

MA27 integer workspace memory

ma27_liw_init_factor

MA27 maximum pivot tolerance

ma27_pivtolmax

MA27 pivot tolerance

ma27_pivtol

MA27 real workspace memory

ma27_la_init_factor

MA57 block size

ma57_block_size

MA57 maximum pivot tolerance

ma57_pivtolmax

MA57 node amalgamation parameter

ma57_node_amalgamation

MA57 pivot order

ma57_pivot_order

MA57 pivot tolerance

ma57_pivtol

MA57 scaling

ma57_automatic_scaling

MA57 small pivot parameter

ma57_small_pivot_flag

MA57 work space memory safety factor

ma57_pre_alloc

MA77 maximum pivot tolerance

ma77_umax

MA77 pivot tolerance

ma77_u

MA86 maximum pivot tolerance

ma86_umax

MA86 pivot tolerance

ma86_u

MA97 maximum pivot tolerance

ma97_umax

MA97 pivot tolerance

ma97_u

Maximum number of refinement steps

max_refinement_steps

Minimum number of refinement steps

min_refinement_steps

MUMPS maximum pivot tolerance

mumps_pivtolmax

MUMPS permuting and scaling

mumps_permuting_scaling

MUMPS pivot order

mumps_pivot_order

MUMPS pivot tolerance

mumps_pivtol

MUMPS scaling

mumps_scaling

MUMPS working space percentage increase

mumps_mem_percent

Constraint multipliers step size method

alpha_for_y

Equality multipliers switch tolerance

alpha_for_y_tol

Recalculate constraint multipliers

recalc_y

Recalculate constraint multipliers tolerance

recalc_y_feas_tol

Assume equality constraints are linear

jac_c_constant

Assume inequality constraints are linear

jac_d_constant

Assume quadratic problem

hessian_constant

Check derivatives for invalid numbers

check_derivatives_for_naninf

Factor for initial bounds relaxation

bound_relax_factor

Fixed variable handling

fixed_variable_treatment

Honor original bounds

honor_original_bounds

Infinity upper bound

nlp_upper_bound_inf

Minus infinity lower bound

nlp_lower_bound_inf

Maximum gradient after NLP scaling

nlp_scaling_max_gradient

NLP scaling method

nlp_scaling_method

Objective function scaling factor

obj_scaling_factor

Output verbosity level

print_level

Print all available algorithmic options

print_options_documentation

Print all user selected options

print_user_options

Status file

Hessian approximation history memory limit

limited_memory_max_history

Hessian approximation successive iterations limit

limited_memory_max_skipping

Method for Hessian computation

hessian_approximation

Bound multipliers reset threshold

bound_mult_reset_threshold

Constraint multipliers reset threshold

constr_mult_reset_threshold

Force start in restoration phase

start_with_resto

Maximum multipliers infeasible problem

expect_infeasible_problem_ytol

Minimum violation infeasible problem

expect_infeasible_problem_ctol

Quickly detect infeasible problem

expect_infeasible_problem

Reduction factor primal dual error

soft_resto_pderror_reduction_factor

Required infeasibility reduction

required_infeasibility_reduction

Use original objective function in restoration phase

evaluate_orig_obj_at_resto_trial

Acceptable complementarity tolerance

acceptable_compl_inf_tol

Acceptable constraint violation tolerance

acceptable_constr_viol_tol

Acceptable dual infeasibility tolerance

acceptable_dual_inf_tol

Acceptable objective change tolerance

acceptable_obj_change_tol

Acceptable relative convergence tolerance

acceptable_tol

Complementarity tolerance

compl_inf_tol

Constraint violation tolerance

constr_viol_tol

Diverging iterates tolerance

diverging_iterates_tol

Dual infeasibility tolerance

dual_inf_tol

Maximum number of acceptable iterations

acceptable_iter

Maximum number of iterations

max_iter

Relative convergence tolerance

tol