Complete list of parameters¶
A set of parameters is available in the table below for fine tuning algorithmic settings. Additional information on each parameter is available by typing $NOMAD_HOME/bin/nomad -h PARAM_NAME
.
Name |
Type |
Argument |
Short description |
Default |
ADD_SEED_TO_FILE_NAMES |
bool |
advanced |
The flag to add seed to the file names |
true |
ANISOTROPIC_MESH |
bool |
advanced |
MADS uses anisotropic mesh for generating directions |
true |
ANISOTROPY_FACTOR |
NOMAD::Double |
advanced |
MADS anisotropy factor for mesh size change |
0.1 |
BB_EXE |
std::string |
basic |
Blackbox executable |
No default |
BB_INPUT_TYPE |
NOMAD::BBInputTypeList |
basic |
The variable blackbox input types |
* R |
BB_MAX_BLOCK_SIZE |
size_t |
advanced |
Size of blocks of points, to be used for parallel evaluations |
1 |
BB_OUTPUT_TYPE |
NOMAD::BBOutputTypeList |
basic |
Type of outputs provided by the blackboxes |
OBJ |
CACHE_FILE |
std::string |
basic |
Cache file name |
No default |
CACHE_SIZE_MAX |
size_t |
advanced |
Maximum number of evaluation points to be stored in the cache |
INF |
DIMENSION |
size_t |
basic |
Dimension of the optimization problem (required) |
0 |
DIRECTION_TYPE |
NOMAD::DirectionTypeList |
advanced |
Direction types for Mads Poll step |
ORTHO 2N |
DIRECTION_TYPE_SECONDARY_POLL |
NOMAD::DirectionTypeList |
advanced |
Direction types for Mads secondary poll |
DOUBLE |
DISPLAY_ALL_EVAL |
bool |
basic |
Flag to display all evaluations |
false |
DISPLAY_DEGREE |
int |
basic |
Level of verbose during execution |
2 |
DISPLAY_HEADER |
size_t |
advanced |
Frequency at which the stats header is displayed |
40 |
DISPLAY_INFEASIBLE |
bool |
advanced |
Flag to display infeasible |
false |
DISPLAY_MAX_STEP_LEVEL |
size_t |
advanced |
Depth of the step after which info is not printed |
20 |
DISPLAY_STATS |
NOMAD::ArrayOfString |
basic |
Format for displaying the evaluation points |
BBE OBJ |
DISPLAY_UNSUCCESSFUL |
bool |
advanced |
Flag to display unsuccessful |
true |
EVAL_OPPORTUNISTIC |
bool |
advanced |
Opportunistic strategy: Terminate evaluations as soon as a success is found |
true |
EVAL_QUEUE_CLEAR |
bool |
advanced |
Opportunistic strategy: Flag to clear EvaluatorControl queue between each run |
true |
EVAL_QUEUE_SORT |
NOMAD::EvalSortType |
advanced |
How to sort points before evaluation |
DIR_LAST_SUCCESS |
EVAL_STATS_FILE |
string |
basic |
The name of the file for stats about evaluations and successes |
No default |
EVAL_SURROGATE_COST |
size_t |
advanced |
Cost of the surrogate function versus the true function |
INF |
EVAL_SURROGATE_OPTIMIZATION |
bool |
advanced |
Use static surrogate as blackbox for optimization |
false |
EVAL_USE_CACHE |
bool |
advanced |
Use cache in algorithms |
true |
FIXED_VARIABLE |
NOMAD::Point |
advanced |
Fix some variables to some specific values |
No default |
FRAME_CENTER_USE_CACHE |
bool |
advanced |
Find best points in the cache and use them as frame centers |
false |
GRANULARITY |
NOMAD::ArrayOfDouble |
advanced |
The granularity of the variables |
No default |
HISTORY_FILE |
std::string |
basic |
The name of the history file |
No default |
H_MAX_0 |
NOMAD::Double |
advanced |
Initial value of hMax. |
NOMAD::INF |
HOT_RESTART_FILE |
std::string |
advanced |
The name of the hot restart file |
hotrestart.txt |
HOT_RESTART_ON_USER_INTERRUPT |
bool |
advanced |
Flag to perform a hot restart on user interrupt |
false |
HOT_RESTART_READ_FILES |
bool |
advanced |
Flag to read hot restart files |
false |
HOT_RESTART_WRITE_FILES |
bool |
advanced |
Flag to write hot restart files |
false |
INITIAL_FRAME_SIZE |
NOMAD::ArrayOfDouble |
advanced |
The initial frame size of MADS |
No default |
INITIAL_MESH_SIZE |
NOMAD::ArrayOfDouble |
advanced |
The initial mesh size of MADS |
No default |
LH_EVAL |
size_t |
basic |
Latin Hypercube Sampling of points (no optimization) |
0 |
LH_SEARCH |
NOMAD::LHSearchType |
basic |
Latin Hypercube Sampling Search method |
No default |
LOWER_BOUND |
NOMAD::ArrayOfDouble |
basic |
The optimization problem lower bounds for each variable |
No default |
MAX_BB_EVAL |
size_t |
basic |
Stopping criterion on the number of blackbox evaluations |
INF |
MAX_BLOCK_EVAL |
size_t |
basic |
Stopping criterion on the number of blocks evaluations |
INF |
MAX_EVAL |
size_t |
advanced |
Stopping criterion on the number of evaluations (blackbox and cache) |
INF |
MAX_ITERATION_PER_MEGAITERATION |
size_t |
advanced |
Maximum number of Iterations to generate for each MegaIteration. |
INF |
MAX_ITERATIONS |
size_t |
advanced |
The maximum number of iterations of the MADS algorithm |
INF |
MAX_SURROGATE_EVAL_OPTIMIZATION |
size_t |
basic |
Stopping criterion on the number of static surrogate evaluations |
INF |
MAX_TIME |
size_t |
basic |
Maximum wall-clock time in seconds |
INF |
MEGA_SEARCH_POLL |
bool |
advanced |
Evaluate points generated from Search and Poll steps all at once |
false |
MIN_FRAME_SIZE |
NOMAD::ArrayOfDouble |
basic |
Termination criterion on minimal frame size of MADS |
No default |
MIN_MESH_SIZE |
NOMAD::ArrayOfDouble |
basic |
Termination criterion on minimal mesh size of MADS |
No default |
NB_THREADS_OPENMP |
int |
advanced |
The number of threads when OpenMP parallel evaluations |
-1 |
NM_DELTA_E |
NOMAD::Double |
advanced |
NM expansion parameter delta_e. |
2 |
NM_DELTA_IC |
NOMAD::Double |
advanced |
NM inside contraction parameter delta_ic. |
-0.5 |
NM_DELTA_OC |
NOMAD::Double |
advanced |
NM outside contraction parameter delta_oc. |
0.5 |
NM_GAMMA |
NOMAD::Double |
advanced |
NM shrink parameter gamma. |
0.5 |
NM_OPTIMIZATION |
bool |
advanced |
Nelder Mead stand alone optimization for constrained and unconstrained pbs |
false |
NM_SEARCH |
bool |
advanced |
Nelder Mead optimization used as a search step for Mads |
true |
NM_SEARCH_MAX_TRIAL_PTS_NFACTOR |
size_t |
advanced |
NM-Mads search stopping criterion. |
80 |
NM_SEARCH_RANK_EPS |
NOMAD::Double |
advanced |
NM-Mads epsilon for the rank of DZ. |
0.01 |
NM_SEARCH_STOP_ON_SUCCESS |
bool |
advanced |
NM-Mads search stops on success. |
false |
NM_SIMPLEX_INCLUDE_FACTOR |
size_t |
advanced |
Construct NM simplex using points in cache. |
8 |
NM_SIMPLEX_INCLUDE_LENGTH |
NOMAD::Double |
advanced |
Construct NM simplex using points in cache. |
INF |
PSD_MADS_ITER_OPPORTUNISTIC |
bool |
advanced |
Opportunistic strategy between the Mads subproblems in PSD-MADS |
true |
PSD_MADS_NB_SUBPROBLEM |
size_t |
advanced |
Number of PSD-MADS subproblems |
INF |
PSD_MADS_NB_VAR_IN_SUBPROBLEM |
size_t |
advanced |
Number of variables in PSD-MADS subproblems |
2 |
PSD_MADS_OPTIMIZATION |
bool |
advanced |
PSD-MADS optimization algorithm |
0 |
PSD_MADS_ORIGINAL |
bool |
advanced |
Use NOMAD 3 strategy for mesh update in PSD-MADS |
false |
PSD_MADS_SUBPROBLEM_MAX_BB_EVAL |
size_t |
advanced |
Max number of evaluations for each subproblem |
INF |
PSD_MADS_SUBPROBLEM_PERCENT_COVERAGE |
NOMAD::Double |
advanced |
Percentage of variables that must be covered in subproblems before updating mesh |
70 |
QUAD_MODEL_DISPLAY |
std::string |
developer |
Display of a model |
No default |
QUAD_MODEL_MAX_BLOCK_SIZE |
size_t |
advanced |
Size of blocks of points, to be used for parallel evaluations |
INF |
QUAD_MODEL_MAX_EVAL |
size_t |
advanced |
Max number of model evaluations for each optimization of the quad model problem |
1000 |
QUAD_MODEL_OPTIMIZATION |
bool |
advanced |
Quad model stand alone optimization for constrained and unconstrained pbs |
false |
QUAD_MODEL_RADIUS_FACTOR |
NOMAD::Double |
developer |
Quadratic model radius factor |
2.0 |
QUAD_MODEL_SEARCH |
bool |
basic |
Quad model search |
true |
QUAD_MODEL_SEARCH_BOUND_REDUCTION_FACTOR |
NOMAD::Double |
basic |
Scale the bounds for the quad model search |
1 |
REJECT_UNKNOWN_PARAMETERS |
bool |
advanced |
Flag to reject unknown parameters when checking validity of parameters |
false |
RHO |
NOMAD::Double |
advanced |
Rho parameter of the progressive barrier |
0.1 |
SEED |
int |
advanced |
The seed for the pseudo-random number generator |
0 |
SGTELIB_MAX_POINTS_FOR_MODEL |
size_t |
developer |
Maximum number of valid points used to build a model |
100 |
SGTELIB_MIN_POINTS_FOR_MODEL |
size_t |
developer |
Minimum number of valid points necessary to build a model |
1 |
SGTELIB_MODEL_DEFINITION |
NOMAD::ArrayOfString |
advanced |
Definition of the Sgtelib model |
No default |
SGTELIB_MODEL_DISPLAY |
std::string |
developer |
Display of a model |
No default |
SGTELIB_MODEL_DIVERSIFICATION |
NOMAD::Double |
developer |
Coefficient of the exploration term in the sgtelib model problem |
0.01 |
SGTELIB_MODEL_EVAL |
bool |
advanced |
Sgtelib Model Sampling of points |
0 |
SGTELIB_MODEL_FEASIBILITY |
NOMAD::SgtelibModelFeasibilityType |
developer |
Method used to model the feasibility of a point |
C |
SGTELIB_MODEL_FORMULATION |
NOMAD::SgtelibModelFormulationType |
developer |
Formulation of the sgtelib model problem |
FS |
SGTELIB_MODEL_MAX_BLOCK_SIZE |
size_t |
advanced |
Size of blocks of points, to be used for parallel evaluations |
INF |
SGTELIB_MODEL_MAX_EVAL |
size_t |
advanced |
Max number of model evaluations for each optimization of the sgtelib model problem |
1000 |
SGTELIB_MODEL_RADIUS_FACTOR |
NOMAD::Double |
developer |
Sgtelib model radius factor |
2.0 |
SGTELIB_MODEL_SEARCH |
bool |
basic |
Model search using Sgtelib |
false |
SGTELIB_MODEL_SEARCH_CANDIDATES_NB |
int |
developer |
Number of candidates returned by the sgtelib model search |
-1 |
SGTELIB_MODEL_SEARCH_EXCLUSION_AREA |
NOMAD::Double |
developer |
Exclusion area for the sgtelib model search around points of the cache |
0.0 |
SGTELIB_MODEL_SEARCH_FILTER |
std::string |
developer |
Methods used in the sgtelib search filter to return several search candidates |
2345 |
SGTELIB_MODEL_SEARCH_TRIALS |
size_t |
developer |
Max number of sgtelib model search failures before going to the poll step |
1 |
SOLUTION_FILE |
std::string |
basic |
The name of the file containing the best feasible solution |
No default |
SPECULATIVE_SEARCH_BASE_FACTOR |
NOMAD::Double |
advanced |
Distance of the MADS speculative search method |
4.0 |
SPECULATIVE_SEARCH |
bool |
basic |
MADS speculative search method |
true |
SPECULATIVE_SEARCH_MAX |
size_t |
advanced |
MADS speculative search method |
1 |
SSD_MADS_ITER_OPPORTUNISTIC |
bool |
advanced |
Opportunistic strategy between the Mads subproblems in SSD-MADS |
true |
SSD_MADS_NB_SUBPROBLEM |
size_t |
advanced |
Number of SSD-MADS subproblems |
INF |
SSD_MADS_NB_VAR_IN_SUBPROBLEM |
size_t |
advanced |
Number of variables in SSD-MADS subproblems |
2 |
SSD_MADS_OPTIMIZATION |
bool |
advanced |
SSD-MADS optimization algorithm |
0 |
SSD_MADS_RESET_VAR_PICKUP_SUBPROBLEM |
bool |
advanced |
Reset random variable pick-up for each subproblem |
false |
SSD_MADS_SUBPROBLEM_MAX_BB_EVAL |
size_t |
advanced |
Max number of evaluations for each subproblem |
INF |
STATS_FILE |
NOMAD::ArrayOfString |
basic |
The name of the stats file |
No default |
STOP_IF_FEASIBLE |
bool |
advanced |
Stop algorithm once a feasible point is obtained |
false |
STOP_IF_PHASE_ONE_SOLUTION |
bool |
advanced |
Stop algorithm once a phase one solution is obtained |
false |
SURROGATE_EXE |
std::string |
advanced |
Static surrogate executable |
No default |
TMP_DIR |
std::string |
advanced |
Directory where to put temporary files |
No default |
UPPER_BOUND |
NOMAD::ArrayOfDouble |
basic |
The optimization problem upper bounds for each variable |
No default |
USER_CALLS_ENABLED |
bool |
advanced |
Controls the automatic calls to user function |
true |
VARIABLE_GROUP |
NOMAD::ListOfVariableGroup |
advanced |
The groups of variables) |
No default |
VNS_MADS_OPTIMIZATION |
bool |
advanced |
VNS MADS stand alone optimization for constrained and unconstrained pbs |
false |
VNS_MADS_SEARCH |
bool |
advanced |
VNS Mads optimization used as a search step for Mads |
false |
VNS_MADS_SEARCH_MAX_TRIAL_PTS_NFACTOR |
size_t |
advanced |
VNS-Mads search stopping criterion. |
100 |
VNS_MADS_SEARCH_TRIGGER |
NOMAD::Double |
advanced |
VNS Mads search trigger |
0.75 |
X0 |
NOMAD::ArrayOfPoint |
basic |
The initial point(s) |
No default |