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inst/nomad/NOMAD_4_5_0_OPTIONS_REFERENCE.md
In crs: Categorical Regression Splines
NOMAD 4.5.0 Option Reference for crs
Generated on: 2026-02-23
Source of truth: vendored NOMAD definition files in src/nomad4_src/src/Attribute
Scope:
- This reference is generated from embedded NOMAD 4.5.0 sources used by crs.
- snomadr(opts=...) passes option names/values through to NOMAD.
- display.nomad.progress=FALSE also sets DISPLAY_DEGREE 0, DISPLAY_ALL_EVAL false, and DISPLAY_UNSUCCESSFUL false.
- nomad.opt in the working directory is read after opts and can override earlier values.
- Option names use NOMAD 4.5.0 terminology directly (for example, MIN_FRAME_SIZE).
Problem Parameters (pbAttributesDefinition.txt)
Total options in this section: 13
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| BB_INPUT_TYPE | NOMAD::BBInputTypeList | * R | The variable blackbox input types |
| DIMENSION | size_t | 0 | Dimension of the optimization problem (required) |
| FIXED_VARIABLE | NOMAD::Point | - | Fix some variables to some specific values |
| GRANULARITY | NOMAD::ArrayOfDouble | - | The granularity of the variables |
| INITIAL_FRAME_SIZE | NOMAD::ArrayOfDouble | - | The initial frame size of MADS |
| INITIAL_MESH_SIZE | NOMAD::ArrayOfDouble | - | The initial mesh size of MADS |
| LOWER_BOUND | NOMAD::ArrayOfDouble | - | The optimization problem lower bounds for each variable |
| MIN_FRAME_SIZE | NOMAD::ArrayOfDouble | - | Termination criterion on minimal frame size of MADS |
| MIN_MESH_SIZE | NOMAD::ArrayOfDouble | - | Termination criterion on minimal mesh size of MADS |
| UPPER_BOUND | NOMAD::ArrayOfDouble | - | The optimization problem upper bounds for each variable |
| VARIABLE_GROUP | NOMAD::ListOfVariableGroup | - | The groups of variables) |
| X0 | NOMAD::ArrayOfPoint | - | The initial point(s) |
| POINT_FORMAT | NOMAD::ArrayOfDouble | - | Format of the doubles for trial points |
Run Parameters (Core) (runAttributesDefinition.txt)
Total options in this section: 35
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| ADD_SEED_TO_FILE_NAMES | bool | true | The flag to add seed to the file names |
| ANISOTROPIC_MESH | bool | true | MADS uses anisotropic mesh for generating directions |
| ANISOTROPY_FACTOR | NOMAD::Double | 0.1 | MADS anisotropy factor for mesh size change |
| SEARCH_METHOD_MESH_PROJECTION | bool | true | Projection on mesh for trial points from a search method |
| DIRECTION_TYPE | NOMAD::DirectionTypeList | ORTHO N+1 QUAD | Direction types for Poll steps |
| DIRECTION_TYPE_SECONDARY_POLL | NOMAD::DirectionTypeList | DOUBLE | Direction types for Mads secondary poll |
| TRIAL_POINT_MAX_ADD_UP | size_t | 0 | Max number of trial points |
| ORTHO_MESH_REFINE_FREQ | size_t | 1 | Control mesh refinement frequency |
| FRAME_CENTER_USE_CACHE | bool | false | Find best points in the cache and use them as frame centers |
| H_MAX_0 | NOMAD::Double | NOMAD::INF | Initial value of hMax. |
| HOT_RESTART_FILE | std::string | hotrestart.txt | The name of the hot restart file |
| HOT_RESTART_ON_USER_INTERRUPT | bool | false | Flag to perform a hot restart on user interrupt |
| HOT_RESTART_READ_FILES | bool | false | Flag to read hot restart files |
| HOT_RESTART_WRITE_FILES | bool | false | Flag to write hot restart files |
| MAX_ITERATIONS | size_t | INF | The maximum number of iterations of the MADS algorithm |
| MAX_ITERATION_PER_MEGAITERATION | size_t | INF | Maximum number of Iterations to generate for each MegaIteration. |
| MAX_TIME | size_t | INF | Maximum wall-clock time in seconds |
| MEGA_SEARCH_POLL | bool | false | Evaluate points generated from Search and Poll steps all at once |
| REJECT_UNKNOWN_PARAMETERS | bool | true | Flag to reject unknown parameters when checking validity of parameters |
| RHO | NOMAD::Double | 0.1 | Rho parameter of the progressive barrier |
| SEED | int | 0 | The seed for the pseudo-random number generator |
| RNG_ALT_SEEDING | bool | false | With this option the seed is used to set xdef |
| SIMPLE_LINE_SEARCH | bool | false | MADS simple line search method complement speculative search |
| SPECULATIVE_SEARCH | bool | true | MADS speculative search method |
| SPECULATIVE_SEARCH_BASE_FACTOR | NOMAD::Double | 4.0 | Distance of the MADS speculative search method |
| SPECULATIVE_SEARCH_MAX | size_t | 1 | MADS speculative search method |
| USER_SEARCH | bool | false | MADS user search method provided as callback function |
| STOP_IF_FEASIBLE | bool | false | Stop algorithm once a feasible point is obtained |
| STOP_IF_PHASE_ONE_SOLUTION | bool | false | Stop algorithm once a phase one solution is obtained |
| USER_CALLS_ENABLED | bool | true | Controls the automatic calls to user function |
| RANDOM_ALGO_SEARCH | bool | false | A random search step for Mads using an algo (several iterations) |
| RANDOM_ALGO_OPTIMIZATION | bool | false | A standalone random optimization algo (several iterations) |
| RANDOM_ALGO_DUMMY_FACTOR | size_t | 1 | Dummy factor for random algo (used as template) |
| H_NORM | NOMAD::HNormType | L2 | Norm type for infeasibility measure (h) computation |
| H_MIN | NOMAD::Double | 0 | Min h value for detecting infeasibility |
Run Parameters (COOP) (runAttributesDefinitionCOOP.txt)
Total options in this section: 3
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| COOP_MADS_OPTIMIZATION | bool | false | COOP-MADS optimization algorithm |
| COOP_MADS_NB_PROBLEM | size_t | 4 | Number of COOP-MADS problems |
| COOP_MADS_OPTIMIZATION_CACHE_SEARCH | bool | true | COOP-MADS cache search for incumbent synchronization |
Run Parameters (Coordinate Search) (runAttributesDefinitionCS.txt)
Total options in this section: 1
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| CS_OPTIMIZATION | bool | false | Coordinate Search optimization |
Run Parameters (DMultiMads) (runAttributesDefinitionDMulti.txt)
Total options in this section: 8
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| DMULTIMADS_EXPANSIONINT_LINESEARCH | bool | false | DMultiMads Expansion integer linesearch |
| DMULTIMADS_QUAD_MODEL_STRATEGY | NOMAD::DMultiMadsQuadSearchType | MULTI | Quad Model search strategies for DMultiMads |
| DMULTIMADS_MIDDLEPOINT_SEARCH | bool | false | DMultiMads Middle Point search |
| DMULTIMADS_MIDDLEPOINT_SEARCH_CACHE_MAX | size_t | 50 | DMultiMads middle point search |
| DMULTIMADS_NM_STRATEGY | NOMAD::DMultiMadsNMSearchType | DOM | Nelder-Mead search strategies for DMultiMads |
| DMULTIMADS_OPTIMIZATION | bool | false | DMultiMads solves multiobjective optimization problems |
| DMULTIMADS_SELECT_INCUMBENT_THRESHOLD | size_t | 1 | Control the choice of the DMultiMads incumbent |
| DMULTIMADS_QMS_PRIOR_COMBINE_OBJ | bool | true | Select compute method for objective of DMultiMads quad model search |
Run Parameters (DiscoMads) (runAttributesDefinitionDisco.txt)
Total options in this section: 8
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| DISCO_MADS_OPTIMIZATION | bool | false | DiscoMads optimization |
| DISCO_MADS_DETECTION_RADIUS | NOMAD::Double | 1.0 | Radius used to reveal discontinuities in DiscoMads |
| DISCO_MADS_LIMIT_RATE | NOMAD::Double | 1 | Limit rate of change used to reveal discontinuities in DiscoMads |
| DISCO_MADS_EXCLUSION_RADIUS | NOMAD::Double | 1 | Radius of exclusion balls around revealing points in DiscoMads |
| DISCO_MADS_REVEALING_POLL_RADIUS | NOMAD::Double | 2.02 | Revealing poll radius in DiscoMads |
| DISCO_MADS_REVEALING_POLL_NB_POINTS | size_t | 1 | Number of random points sampled by the revealing poll in DiscoMads |
| DISCO_MADS_HID_CONST | bool | false | Use DiscoMADS to reveal and escape hidden constraints regions |
| DISCO_MADS_HID_CONST_OUTPUT_VALUE | NOMAD::Double | 1E20 | Value attributed to objective function and PB constraints for failed evaluations |
Run Parameters (IBEX) (runAttributesDefinitionIBEX.txt)
Total options in this section: 4
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| USE_IBEX | bool | false | Boolean to determine if we want to use the functionnalities of IBEX |
| SYSTEM_FILE_NAME | string | - | File with the constraints |
| SET_FILE | bool | false | Boolean to determine if the file of the set is already created |
| SET_FILE_NAME | string | - | File to load with the set |
Run Parameters (Latin Hypercube) (runAttributesDefinitionLH.txt)
Total options in this section: 2
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| LH_EVAL | size_t | 0 | Latin Hypercube Sampling of points (no optimization) |
| LH_SEARCH | NOMAD::LHSearchType | - | Latin Hypercube Sampling Search method |
Run Parameters (Nelder-Mead) (runAttributesDefinitionNM.txt)
Total options in this section: 11
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| NM_OPTIMIZATION | bool | false | Nelder Mead stand alone optimization for constrained and unconstrained pbs |
| NM_SEARCH | bool | true | Nelder Mead optimization used as a search step for Mads |
| NM_SIMPLEX_INCLUDE_LENGTH | NOMAD::Double | INF | Construct NM simplex using points in cache. |
| NM_SIMPLEX_INCLUDE_FACTOR | size_t | 8 | Construct NM simplex using points in cache. |
| NM_DELTA_E | NOMAD::Double | 2 | NM expansion parameter delta_e. |
| NM_DELTA_IC | NOMAD::Double | -0.5 | NM inside contraction parameter delta_ic. |
| NM_DELTA_OC | NOMAD::Double | 0.5 | NM outside contraction parameter delta_oc. |
| NM_GAMMA | NOMAD::Double | 0.5 | NM shrink parameter gamma. |
| NM_SEARCH_MAX_TRIAL_PTS_NFACTOR | size_t | 80 | NM-Mads search stopping criterion. |
| NM_SEARCH_RANK_EPS | NOMAD::Double | 0.01 | NM-Mads epsilon for the rank of DZ. |
| NM_SEARCH_STOP_ON_SUCCESS | bool | false | NM-Mads search stops on success. |
Run Parameters (PSD-Mads) (runAttributesDefinitionPSDSSD.txt)
Total options in this section: 6
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| PSD_MADS_OPTIMIZATION | bool | 0 | PSD-MADS optimization algorithm |
| PSD_MADS_NB_VAR_IN_SUBPROBLEM | size_t | 2 | Number of variables in PSD-MADS subproblems |
| PSD_MADS_NB_SUBPROBLEM | size_t | INF | Number of PSD-MADS subproblems |
| PSD_MADS_ITER_OPPORTUNISTIC | bool | true | Opportunistic strategy between the Mads subproblems in PSD-MADS |
| PSD_MADS_ORIGINAL | bool | false | Use NOMAD 3 strategy for mesh update in PSD-MADS |
| PSD_MADS_SUBPROBLEM_PERCENT_COVERAGE | NOMAD::Double | 70 | Percentage of variables that must be covered in subproblems before updating mesh |
Run Parameters (QP Solver) (runAttributesDefinitionQPSolver.txt)
Total options in this section: 20
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| QP_OPTIMIZATION | bool | false | Quad model stand alone QP optimization for constrained and unconstrained pbs |
| QP_SEARCH | bool | false | A quad model based search step for Mads using a QP solver |
| QP_SelectAlgo | size_t | 0 | Select the algorithm for QP solver |
| QP_maxIter | size_t | 20 | QPSolver outter loop iteration limit |
| QP_tolDistDX | NOMAD::Double | -1.0 | A quad model based search step for Mads using a QP solver |
| QP_absoluteTol | NOMAD::Double | 1e-3 | A quad model based search step for Mads using a QP solver |
| QP_tolCond | NOMAD::Double | 1e-15 | A quad model based search step for Mads using a QP solver |
| QP_tolMesh | NOMAD::Double | 1.0 | A quad model based search step for Mads using a QP solver |
| QP_relativeTol | NOMAD::Double | 1e-3 | A quad model based search step for Mads using a QP solver |
| QP_verbose | bool | false | A quad model based search step for Mads using a QP solver |
| QP_verboseFull | bool | false | A quad model based search step for Mads using a QP solver |
| QP_AugLag_mu0 | NOMAD::Double | 0.5 | A quad model based search step for Mads using a QP solver |
| QP_AugLag_muDecrease | NOMAD::Double | 2 | A quad model based search step for Mads using a QP solver |
| QP_AugLag_eta0 | NOMAD::Double | 1.0 | A quad model based search step for Mads using a QP solver |
| QP_AugLag_omega0 | NOMAD::Double | 1.0 | A quad model based search step for Mads using a QP solver |
| QP_AugLag_maxIterInner | size_t | 50 | QPSolver inner iteration limit for the subproblem |
| QP_AugLag_tolDistDXInner | NOMAD::Double | 1e-15 | A quad model based search step for Mads using a QP solver |
| QP_AugLag_maxSuccessivFail | size_t | 3 | A quad model based search step for Mads using a QP solver |
| QP_AugLag_successRatio | NOMAD::Double | 0.99 | A quad model based search step for Mads using a QP solver |
| QP_SEARCH_MODEL_BOX_SIZE_LIMIT | NOMAD::Double | 0 | QP solver generates trial points if bounds box size is above limit |
Run Parameters (Quadratic Model) (runAttributesDefinitionQuadModel.txt)
Total options in this section: 8
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| QUAD_MODEL_SEARCH | bool | true | Quad model search |
| QUAD_MODEL_SEARCH_SIMPLE_MADS | bool | false | Quad model search using a simpler version of Mads |
| QUAD_MODEL_SEARCH_BOUND_REDUCTION_FACTOR | NOMAD::Double | 1 | Scale the bounds for the quad model search |
| QUAD_MODEL_DISPLAY | std::string | - | Display of a model |
| QUAD_MODEL_OPTIMIZATION | bool | false | Quad model stand alone optimization for constrained and unconstrained pbs |
| QUAD_MODEL_SEARCH_BOX_FACTOR | NOMAD::Double | 4.0 | Quadratic model search point selection factor |
| QUAD_MODEL_BOX_FACTOR | NOMAD::Double | 4.0 | Quadratic model points selection box factor |
| QUAD_MODEL_SEARCH_FORCE_EB | bool | false | Quadratic model search optimization using extreme barrier |
Run Parameters (Sgtelib Model) (runAttributesDefinitionSgtelibModel.txt)
Total options in this section: 14
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| SGTELIB_MODEL_EVAL | bool | 0 | Sgtelib Model Sampling of points |
| SGTELIB_MODEL_SEARCH | bool | false | Model search using Sgtelib |
| SGTELIB_MODEL_DISPLAY | std::string | - | Display of a model |
| SGTELIB_MODEL_DEFINITION | NOMAD::ArrayOfString | - | Definition of the Sgtelib model |
| SGTELIB_MODEL_SEARCH_TRIALS | size_t | 1 | Max number of sgtelib model search failures before going to the poll step |
| SGTELIB_MODEL_FORMULATION | NOMAD::SgtelibModelFormulationType | FS | Formulation of the sgtelib model problem |
| SGTELIB_MODEL_FEASIBILITY | NOMAD::SgtelibModelFeasibilityType | C | Method used to model the feasibility of a point |
| SGTELIB_MODEL_DIVERSIFICATION | NOMAD::Double | 0.01 | Coefficient of the exploration term in the sgtelib model problem |
| SGTELIB_MODEL_SEARCH_EXCLUSION_AREA | NOMAD::Double | 0.0 | Exclusion area for the sgtelib model search around points of the cache |
| SGTELIB_MODEL_SEARCH_CANDIDATES_NB | int | -1 | Number of candidates returned by the sgtelib model search |
| SGTELIB_MIN_POINTS_FOR_MODEL | size_t | 1 | Minimum number of valid points necessary to build a model |
| SGTELIB_MAX_POINTS_FOR_MODEL | size_t | 500 | Maximum number of valid points used to build a model |
| SGTELIB_MODEL_SEARCH_FILTER | std::string | 2345 | Methods used in the sgtelib search filter to return several search candidates |
| SGTELIB_MODEL_RADIUS_FACTOR | NOMAD::Double | 2.0 | Sgtelib model radius factor |
Run Parameters (VNS) (runAttributesDefinitionVNS.txt)
Total options in this section: 7
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| VNS_MADS_OPTIMIZATION | bool | false | VNS MADS stand alone optimization for constrained and unconstrained pbs |
| VNSMART_MADS_SEARCH | bool | false | VNS Mads search under condition of consecutive fails |
| VNSMART_MADS_SEARCH_THRESHOLD | int | 3 | Threshold for VNS (SMART) Mads search |
| VNS_MADS_SEARCH | bool | false | VNS Mads optimization used as a search step for Mads |
| VNS_MADS_SEARCH_TRIGGER | NOMAD::Double | 0.75 | VNS Mads search trigger |
| VNS_MADS_SEARCH_WITH_SURROGATE | bool | false | VNS Mads search with surrogate |
| VNS_MADS_SEARCH_MAX_TRIAL_PTS_NFACTOR | size_t | 100 | VNS-Mads search stopping criterion. |
Evaluation Parameters (evalAttributesDefinition.txt)
Total options in this section: 5
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| BB_EVAL_FORMAT | NOMAD::ArrayOfDouble | - | Format of the doubles sent to the blackbox evaluator |
| BB_EXE | std::string | - | Blackbox executable |
| BB_REDIRECTION | bool | true | Blackbox executable redirection for outputs |
| BB_OUTPUT_TYPE | NOMAD::BBOutputTypeList | OBJ | Type of outputs provided by the blackboxes |
| SURROGATE_EXE | std::string | - | Static surrogate executable |
Display Parameters (displayAttributesDefinition.txt)
Total options in this section: 15
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| DISPLAY_ALL_EVAL | bool | false | Flag to display all evaluations |
| DISPLAY_DEGREE | int | 2 | Level of verbose during execution |
| DISPLAY_HEADER | size_t | 40 | Frequency at which the stats header is displayed |
| DISPLAY_INFEASIBLE | bool | true | Flag to display infeasible |
| DISPLAY_MAX_STEP_LEVEL | size_t | 20 | Depth of the step after which info is not printed |
| DISPLAY_STATS | NOMAD::ArrayOfString | BBE OBJ | Format for displaying the evaluation points |
| DISPLAY_FAILED | bool | false | Flag to display failed evaluation |
| DISPLAY_UNSUCCESSFUL | bool | false | Flag to display unsuccessful |
| STATS_FILE | NOMAD::ArrayOfString | - | The name of the stats file |
| EVAL_STATS_FILE | string | - | The name of the file for stats about evaluations and successes |
| SOL_FORMAT | NOMAD::ArrayOfDouble | - | Internal parameter for format of the solution |
| OBJ_WIDTH | size_t | 0 | Internal parameter for character width of the objective |
| HISTORY_FILE | std::string | - | The name of the history file |
| SOLUTION_FILE | std::string | - | The name of the file containing the best feasible solution |
| SOLUTION_FILE_FINAL | bool | false | Flag to decide when to write best feasible solution |
Cache Parameters (cacheAttributesDefinition.txt)
Total options in this section: 2
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| CACHE_FILE | std::string | "" | Cache file name |
| CACHE_SIZE_MAX | size_t | INF | Maximum number of evaluation points to be stored in the cache |
Evaluator Control Parameters (evaluatorControlAttributesDefinition.txt)
Total options in this section: 6
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| EVAL_OPPORTUNISTIC | bool | true | Opportunistic strategy: Terminate evaluations as soon as a success is found |
| EVAL_SURROGATE_OPTIMIZATION | bool | false | Use static surrogate as blackbox for optimization |
| EVAL_USE_CACHE | bool | true | Use cache in algorithms |
| EVAL_QUEUE_SORT | NOMAD::EvalSortType | QUADRATIC_MODEL | How to sort points before evaluation |
| PSD_MADS_SUBPROBLEM_MAX_BB_EVAL | size_t | INF | Max number of evaluations for each subproblem |
| SUBPROBLEM_MAX_BB_EVAL | size_t | INF | Internal parameter for PSD_MADS_SUBPROBLEM_MAX_BB_EVAL |
Evaluator Control Global Parameters (evaluatorControlGlobalAttributesDefinition.txt)
Total options in this section: 17
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| BB_MAX_BLOCK_SIZE | size_t | 1 | Size of blocks of points, to be used for parallel evaluations |
| SURROGATE_MAX_BLOCK_SIZE | size_t | 1 | Size of blocks of points, to be used for parallel evaluations |
| EVAL_QUEUE_CLEAR | bool | true | Opportunistic strategy: Flag to clear EvaluatorControl queue between each run |
| EVAL_SURROGATE_COST | size_t | INF | Cost of the surrogate function versus the true function |
| MAX_BB_EVAL | size_t | INF | Stopping criterion on the number of blackbox evaluations |
| MAX_BLOCK_EVAL | size_t | INF | Stopping criterion on the number of blocks evaluations |
| MAX_EVAL | size_t | INF | Stopping criterion on the number of evaluations (blackbox and cache) |
| MAX_SURROGATE_EVAL_OPTIMIZATION | size_t | INF | Stopping criterion on the number of static surrogate evaluations |
| MODEL_MAX_BLOCK_SIZE | size_t | INF | Internal parameter for QUAD_MODEL_MAX_BLOCK_SIZE and SGTELIB_MODEL_MAX_BLOCK_SIZE |
| MODEL_MAX_EVAL | size_t | 1000 | Internal parameter for QUAD_MODEL_MAX_EVAL and SGTELIB_MODEL_MAX_EVAL |
| QUAD_MODEL_MAX_BLOCK_SIZE | size_t | INF | Size of blocks of points, to be used for parallel evaluations |
| QUAD_MODEL_MAX_EVAL | size_t | 2000 | Max number of model evaluations for optimization of the quad model problem |
| SGTELIB_MODEL_MAX_BLOCK_SIZE | size_t | INF | Size of blocks of points, to be used for parallel evaluations |
| SGTELIB_MODEL_MAX_EVAL | size_t | 2000 | Max number of model evaluations for each optimization of the sgtelib model problem |
| TMP_DIR | std::string | - | Directory where to put temporary files |
| USE_CACHE_FILE_FOR_RERUN | bool | false | Cache file for rerun |
| NB_THREADS_PARALLEL_EVAL | int | 1 | Max number of threads used for parallel evaluations of each algorithm |
Totals
- Total option entries across all definition files: 185
- To inspect option help at runtime:
snomadr(information = list("help" = "-h"))
- To inspect a specific option at runtime:
snomadr(information = list("help" = "-h OPTION_NAME"))
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NOMAD 4.5.0 Option Reference for crs
Generated on: 2026-02-23
Source of truth: vendored NOMAD definition files in src/nomad4_src/src/Attribute
Scope:
- This reference is generated from embedded NOMAD 4.5.0 sources used by crs.
- snomadr(opts=...) passes option names/values through to NOMAD.
- display.nomad.progress=FALSE also sets DISPLAY_DEGREE 0, DISPLAY_ALL_EVAL false, and DISPLAY_UNSUCCESSFUL false.
- nomad.opt in the working directory is read after opts and can override earlier values.
- Option names use NOMAD 4.5.0 terminology directly (for example, MIN_FRAME_SIZE).
Problem Parameters (pbAttributesDefinition.txt)
Total options in this section: 13
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| BB_INPUT_TYPE | NOMAD::BBInputTypeList | * R | The variable blackbox input types |
| DIMENSION | size_t | 0 | Dimension of the optimization problem (required) |
| FIXED_VARIABLE | NOMAD::Point | - | Fix some variables to some specific values |
| GRANULARITY | NOMAD::ArrayOfDouble | - | The granularity of the variables |
| INITIAL_FRAME_SIZE | NOMAD::ArrayOfDouble | - | The initial frame size of MADS |
| INITIAL_MESH_SIZE | NOMAD::ArrayOfDouble | - | The initial mesh size of MADS |
| LOWER_BOUND | NOMAD::ArrayOfDouble | - | The optimization problem lower bounds for each variable |
| MIN_FRAME_SIZE | NOMAD::ArrayOfDouble | - | Termination criterion on minimal frame size of MADS |
| MIN_MESH_SIZE | NOMAD::ArrayOfDouble | - | Termination criterion on minimal mesh size of MADS |
| UPPER_BOUND | NOMAD::ArrayOfDouble | - | The optimization problem upper bounds for each variable |
| VARIABLE_GROUP | NOMAD::ListOfVariableGroup | - | The groups of variables) |
| X0 | NOMAD::ArrayOfPoint | - | The initial point(s) |
| POINT_FORMAT | NOMAD::ArrayOfDouble | - | Format of the doubles for trial points |
Run Parameters (Core) (runAttributesDefinition.txt)
Total options in this section: 35
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| ADD_SEED_TO_FILE_NAMES | bool | true | The flag to add seed to the file names |
| ANISOTROPIC_MESH | bool | true | MADS uses anisotropic mesh for generating directions |
| ANISOTROPY_FACTOR | NOMAD::Double | 0.1 | MADS anisotropy factor for mesh size change |
| SEARCH_METHOD_MESH_PROJECTION | bool | true | Projection on mesh for trial points from a search method |
| DIRECTION_TYPE | NOMAD::DirectionTypeList | ORTHO N+1 QUAD | Direction types for Poll steps |
| DIRECTION_TYPE_SECONDARY_POLL | NOMAD::DirectionTypeList | DOUBLE | Direction types for Mads secondary poll |
| TRIAL_POINT_MAX_ADD_UP | size_t | 0 | Max number of trial points |
| ORTHO_MESH_REFINE_FREQ | size_t | 1 | Control mesh refinement frequency |
| FRAME_CENTER_USE_CACHE | bool | false | Find best points in the cache and use them as frame centers |
| H_MAX_0 | NOMAD::Double | NOMAD::INF | Initial value of hMax. |
| HOT_RESTART_FILE | std::string | hotrestart.txt | The name of the hot restart file |
| HOT_RESTART_ON_USER_INTERRUPT | bool | false | Flag to perform a hot restart on user interrupt |
| HOT_RESTART_READ_FILES | bool | false | Flag to read hot restart files |
| HOT_RESTART_WRITE_FILES | bool | false | Flag to write hot restart files |
| MAX_ITERATIONS | size_t | INF | The maximum number of iterations of the MADS algorithm |
| MAX_ITERATION_PER_MEGAITERATION | size_t | INF | Maximum number of Iterations to generate for each MegaIteration. |
| MAX_TIME | size_t | INF | Maximum wall-clock time in seconds |
| MEGA_SEARCH_POLL | bool | false | Evaluate points generated from Search and Poll steps all at once |
| REJECT_UNKNOWN_PARAMETERS | bool | true | Flag to reject unknown parameters when checking validity of parameters |
| RHO | NOMAD::Double | 0.1 | Rho parameter of the progressive barrier |
| SEED | int | 0 | The seed for the pseudo-random number generator |
| RNG_ALT_SEEDING | bool | false | With this option the seed is used to set xdef |
| SIMPLE_LINE_SEARCH | bool | false | MADS simple line search method complement speculative search |
| SPECULATIVE_SEARCH | bool | true | MADS speculative search method |
| SPECULATIVE_SEARCH_BASE_FACTOR | NOMAD::Double | 4.0 | Distance of the MADS speculative search method |
| SPECULATIVE_SEARCH_MAX | size_t | 1 | MADS speculative search method |
| USER_SEARCH | bool | false | MADS user search method provided as callback function |
| STOP_IF_FEASIBLE | bool | false | Stop algorithm once a feasible point is obtained |
| STOP_IF_PHASE_ONE_SOLUTION | bool | false | Stop algorithm once a phase one solution is obtained |
| USER_CALLS_ENABLED | bool | true | Controls the automatic calls to user function |
| RANDOM_ALGO_SEARCH | bool | false | A random search step for Mads using an algo (several iterations) |
| RANDOM_ALGO_OPTIMIZATION | bool | false | A standalone random optimization algo (several iterations) |
| RANDOM_ALGO_DUMMY_FACTOR | size_t | 1 | Dummy factor for random algo (used as template) |
| H_NORM | NOMAD::HNormType | L2 | Norm type for infeasibility measure (h) computation |
| H_MIN | NOMAD::Double | 0 | Min h value for detecting infeasibility |
Run Parameters (COOP) (runAttributesDefinitionCOOP.txt)
Total options in this section: 3
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| COOP_MADS_OPTIMIZATION | bool | false | COOP-MADS optimization algorithm |
| COOP_MADS_NB_PROBLEM | size_t | 4 | Number of COOP-MADS problems |
| COOP_MADS_OPTIMIZATION_CACHE_SEARCH | bool | true | COOP-MADS cache search for incumbent synchronization |
Run Parameters (Coordinate Search) (runAttributesDefinitionCS.txt)
Total options in this section: 1
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| CS_OPTIMIZATION | bool | false | Coordinate Search optimization |
Run Parameters (DMultiMads) (runAttributesDefinitionDMulti.txt)
Total options in this section: 8
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| DMULTIMADS_EXPANSIONINT_LINESEARCH | bool | false | DMultiMads Expansion integer linesearch |
| DMULTIMADS_QUAD_MODEL_STRATEGY | NOMAD::DMultiMadsQuadSearchType | MULTI | Quad Model search strategies for DMultiMads |
| DMULTIMADS_MIDDLEPOINT_SEARCH | bool | false | DMultiMads Middle Point search |
| DMULTIMADS_MIDDLEPOINT_SEARCH_CACHE_MAX | size_t | 50 | DMultiMads middle point search |
| DMULTIMADS_NM_STRATEGY | NOMAD::DMultiMadsNMSearchType | DOM | Nelder-Mead search strategies for DMultiMads |
| DMULTIMADS_OPTIMIZATION | bool | false | DMultiMads solves multiobjective optimization problems |
| DMULTIMADS_SELECT_INCUMBENT_THRESHOLD | size_t | 1 | Control the choice of the DMultiMads incumbent |
| DMULTIMADS_QMS_PRIOR_COMBINE_OBJ | bool | true | Select compute method for objective of DMultiMads quad model search |
Run Parameters (DiscoMads) (runAttributesDefinitionDisco.txt)
Total options in this section: 8
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| DISCO_MADS_OPTIMIZATION | bool | false | DiscoMads optimization |
| DISCO_MADS_DETECTION_RADIUS | NOMAD::Double | 1.0 | Radius used to reveal discontinuities in DiscoMads |
| DISCO_MADS_LIMIT_RATE | NOMAD::Double | 1 | Limit rate of change used to reveal discontinuities in DiscoMads |
| DISCO_MADS_EXCLUSION_RADIUS | NOMAD::Double | 1 | Radius of exclusion balls around revealing points in DiscoMads |
| DISCO_MADS_REVEALING_POLL_RADIUS | NOMAD::Double | 2.02 | Revealing poll radius in DiscoMads |
| DISCO_MADS_REVEALING_POLL_NB_POINTS | size_t | 1 | Number of random points sampled by the revealing poll in DiscoMads |
| DISCO_MADS_HID_CONST | bool | false | Use DiscoMADS to reveal and escape hidden constraints regions |
| DISCO_MADS_HID_CONST_OUTPUT_VALUE | NOMAD::Double | 1E20 | Value attributed to objective function and PB constraints for failed evaluations |
Run Parameters (IBEX) (runAttributesDefinitionIBEX.txt)
Total options in this section: 4
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| USE_IBEX | bool | false | Boolean to determine if we want to use the functionnalities of IBEX |
| SYSTEM_FILE_NAME | string | - | File with the constraints |
| SET_FILE | bool | false | Boolean to determine if the file of the set is already created |
| SET_FILE_NAME | string | - | File to load with the set |
Run Parameters (Latin Hypercube) (runAttributesDefinitionLH.txt)
Total options in this section: 2
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| LH_EVAL | size_t | 0 | Latin Hypercube Sampling of points (no optimization) |
| LH_SEARCH | NOMAD::LHSearchType | - | Latin Hypercube Sampling Search method |
Run Parameters (Nelder-Mead) (runAttributesDefinitionNM.txt)
Total options in this section: 11
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| NM_OPTIMIZATION | bool | false | Nelder Mead stand alone optimization for constrained and unconstrained pbs |
| NM_SEARCH | bool | true | Nelder Mead optimization used as a search step for Mads |
| NM_SIMPLEX_INCLUDE_LENGTH | NOMAD::Double | INF | Construct NM simplex using points in cache. |
| NM_SIMPLEX_INCLUDE_FACTOR | size_t | 8 | Construct NM simplex using points in cache. |
| NM_DELTA_E | NOMAD::Double | 2 | NM expansion parameter delta_e. |
| NM_DELTA_IC | NOMAD::Double | -0.5 | NM inside contraction parameter delta_ic. |
| NM_DELTA_OC | NOMAD::Double | 0.5 | NM outside contraction parameter delta_oc. |
| NM_GAMMA | NOMAD::Double | 0.5 | NM shrink parameter gamma. |
| NM_SEARCH_MAX_TRIAL_PTS_NFACTOR | size_t | 80 | NM-Mads search stopping criterion. |
| NM_SEARCH_RANK_EPS | NOMAD::Double | 0.01 | NM-Mads epsilon for the rank of DZ. |
| NM_SEARCH_STOP_ON_SUCCESS | bool | false | NM-Mads search stops on success. |
Run Parameters (PSD-Mads) (runAttributesDefinitionPSDSSD.txt)
Total options in this section: 6
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| PSD_MADS_OPTIMIZATION | bool | 0 | PSD-MADS optimization algorithm |
| PSD_MADS_NB_VAR_IN_SUBPROBLEM | size_t | 2 | Number of variables in PSD-MADS subproblems |
| PSD_MADS_NB_SUBPROBLEM | size_t | INF | Number of PSD-MADS subproblems |
| PSD_MADS_ITER_OPPORTUNISTIC | bool | true | Opportunistic strategy between the Mads subproblems in PSD-MADS |
| PSD_MADS_ORIGINAL | bool | false | Use NOMAD 3 strategy for mesh update in PSD-MADS |
| PSD_MADS_SUBPROBLEM_PERCENT_COVERAGE | NOMAD::Double | 70 | Percentage of variables that must be covered in subproblems before updating mesh |
Run Parameters (QP Solver) (runAttributesDefinitionQPSolver.txt)
Total options in this section: 20
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| QP_OPTIMIZATION | bool | false | Quad model stand alone QP optimization for constrained and unconstrained pbs |
| QP_SEARCH | bool | false | A quad model based search step for Mads using a QP solver |
| QP_SelectAlgo | size_t | 0 | Select the algorithm for QP solver |
| QP_maxIter | size_t | 20 | QPSolver outter loop iteration limit |
| QP_tolDistDX | NOMAD::Double | -1.0 | A quad model based search step for Mads using a QP solver |
| QP_absoluteTol | NOMAD::Double | 1e-3 | A quad model based search step for Mads using a QP solver |
| QP_tolCond | NOMAD::Double | 1e-15 | A quad model based search step for Mads using a QP solver |
| QP_tolMesh | NOMAD::Double | 1.0 | A quad model based search step for Mads using a QP solver |
| QP_relativeTol | NOMAD::Double | 1e-3 | A quad model based search step for Mads using a QP solver |
| QP_verbose | bool | false | A quad model based search step for Mads using a QP solver |
| QP_verboseFull | bool | false | A quad model based search step for Mads using a QP solver |
| QP_AugLag_mu0 | NOMAD::Double | 0.5 | A quad model based search step for Mads using a QP solver |
| QP_AugLag_muDecrease | NOMAD::Double | 2 | A quad model based search step for Mads using a QP solver |
| QP_AugLag_eta0 | NOMAD::Double | 1.0 | A quad model based search step for Mads using a QP solver |
| QP_AugLag_omega0 | NOMAD::Double | 1.0 | A quad model based search step for Mads using a QP solver |
| QP_AugLag_maxIterInner | size_t | 50 | QPSolver inner iteration limit for the subproblem |
| QP_AugLag_tolDistDXInner | NOMAD::Double | 1e-15 | A quad model based search step for Mads using a QP solver |
| QP_AugLag_maxSuccessivFail | size_t | 3 | A quad model based search step for Mads using a QP solver |
| QP_AugLag_successRatio | NOMAD::Double | 0.99 | A quad model based search step for Mads using a QP solver |
| QP_SEARCH_MODEL_BOX_SIZE_LIMIT | NOMAD::Double | 0 | QP solver generates trial points if bounds box size is above limit |
Run Parameters (Quadratic Model) (runAttributesDefinitionQuadModel.txt)
Total options in this section: 8
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| QUAD_MODEL_SEARCH | bool | true | Quad model search |
| QUAD_MODEL_SEARCH_SIMPLE_MADS | bool | false | Quad model search using a simpler version of Mads |
| QUAD_MODEL_SEARCH_BOUND_REDUCTION_FACTOR | NOMAD::Double | 1 | Scale the bounds for the quad model search |
| QUAD_MODEL_DISPLAY | std::string | - | Display of a model |
| QUAD_MODEL_OPTIMIZATION | bool | false | Quad model stand alone optimization for constrained and unconstrained pbs |
| QUAD_MODEL_SEARCH_BOX_FACTOR | NOMAD::Double | 4.0 | Quadratic model search point selection factor |
| QUAD_MODEL_BOX_FACTOR | NOMAD::Double | 4.0 | Quadratic model points selection box factor |
| QUAD_MODEL_SEARCH_FORCE_EB | bool | false | Quadratic model search optimization using extreme barrier |
Run Parameters (Sgtelib Model) (runAttributesDefinitionSgtelibModel.txt)
Total options in this section: 14
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| SGTELIB_MODEL_EVAL | bool | 0 | Sgtelib Model Sampling of points |
| SGTELIB_MODEL_SEARCH | bool | false | Model search using Sgtelib |
| SGTELIB_MODEL_DISPLAY | std::string | - | Display of a model |
| SGTELIB_MODEL_DEFINITION | NOMAD::ArrayOfString | - | Definition of the Sgtelib model |
| SGTELIB_MODEL_SEARCH_TRIALS | size_t | 1 | Max number of sgtelib model search failures before going to the poll step |
| SGTELIB_MODEL_FORMULATION | NOMAD::SgtelibModelFormulationType | FS | Formulation of the sgtelib model problem |
| SGTELIB_MODEL_FEASIBILITY | NOMAD::SgtelibModelFeasibilityType | C | Method used to model the feasibility of a point |
| SGTELIB_MODEL_DIVERSIFICATION | NOMAD::Double | 0.01 | Coefficient of the exploration term in the sgtelib model problem |
| SGTELIB_MODEL_SEARCH_EXCLUSION_AREA | NOMAD::Double | 0.0 | Exclusion area for the sgtelib model search around points of the cache |
| SGTELIB_MODEL_SEARCH_CANDIDATES_NB | int | -1 | Number of candidates returned by the sgtelib model search |
| SGTELIB_MIN_POINTS_FOR_MODEL | size_t | 1 | Minimum number of valid points necessary to build a model |
| SGTELIB_MAX_POINTS_FOR_MODEL | size_t | 500 | Maximum number of valid points used to build a model |
| SGTELIB_MODEL_SEARCH_FILTER | std::string | 2345 | Methods used in the sgtelib search filter to return several search candidates |
| SGTELIB_MODEL_RADIUS_FACTOR | NOMAD::Double | 2.0 | Sgtelib model radius factor |
Run Parameters (VNS) (runAttributesDefinitionVNS.txt)
Total options in this section: 7
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| VNS_MADS_OPTIMIZATION | bool | false | VNS MADS stand alone optimization for constrained and unconstrained pbs |
| VNSMART_MADS_SEARCH | bool | false | VNS Mads search under condition of consecutive fails |
| VNSMART_MADS_SEARCH_THRESHOLD | int | 3 | Threshold for VNS (SMART) Mads search |
| VNS_MADS_SEARCH | bool | false | VNS Mads optimization used as a search step for Mads |
| VNS_MADS_SEARCH_TRIGGER | NOMAD::Double | 0.75 | VNS Mads search trigger |
| VNS_MADS_SEARCH_WITH_SURROGATE | bool | false | VNS Mads search with surrogate |
| VNS_MADS_SEARCH_MAX_TRIAL_PTS_NFACTOR | size_t | 100 | VNS-Mads search stopping criterion. |
Evaluation Parameters (evalAttributesDefinition.txt)
Total options in this section: 5
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| BB_EVAL_FORMAT | NOMAD::ArrayOfDouble | - | Format of the doubles sent to the blackbox evaluator |
| BB_EXE | std::string | - | Blackbox executable |
| BB_REDIRECTION | bool | true | Blackbox executable redirection for outputs |
| BB_OUTPUT_TYPE | NOMAD::BBOutputTypeList | OBJ | Type of outputs provided by the blackboxes |
| SURROGATE_EXE | std::string | - | Static surrogate executable |
Display Parameters (displayAttributesDefinition.txt)
Total options in this section: 15
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| DISPLAY_ALL_EVAL | bool | false | Flag to display all evaluations |
| DISPLAY_DEGREE | int | 2 | Level of verbose during execution |
| DISPLAY_HEADER | size_t | 40 | Frequency at which the stats header is displayed |
| DISPLAY_INFEASIBLE | bool | true | Flag to display infeasible |
| DISPLAY_MAX_STEP_LEVEL | size_t | 20 | Depth of the step after which info is not printed |
| DISPLAY_STATS | NOMAD::ArrayOfString | BBE OBJ | Format for displaying the evaluation points |
| DISPLAY_FAILED | bool | false | Flag to display failed evaluation |
| DISPLAY_UNSUCCESSFUL | bool | false | Flag to display unsuccessful |
| STATS_FILE | NOMAD::ArrayOfString | - | The name of the stats file |
| EVAL_STATS_FILE | string | - | The name of the file for stats about evaluations and successes |
| SOL_FORMAT | NOMAD::ArrayOfDouble | - | Internal parameter for format of the solution |
| OBJ_WIDTH | size_t | 0 | Internal parameter for character width of the objective |
| HISTORY_FILE | std::string | - | The name of the history file |
| SOLUTION_FILE | std::string | - | The name of the file containing the best feasible solution |
| SOLUTION_FILE_FINAL | bool | false | Flag to decide when to write best feasible solution |
Cache Parameters (cacheAttributesDefinition.txt)
Total options in this section: 2
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| CACHE_FILE | std::string | "" | Cache file name |
| CACHE_SIZE_MAX | size_t | INF | Maximum number of evaluation points to be stored in the cache |
Evaluator Control Parameters (evaluatorControlAttributesDefinition.txt)
Total options in this section: 6
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| EVAL_OPPORTUNISTIC | bool | true | Opportunistic strategy: Terminate evaluations as soon as a success is found |
| EVAL_SURROGATE_OPTIMIZATION | bool | false | Use static surrogate as blackbox for optimization |
| EVAL_USE_CACHE | bool | true | Use cache in algorithms |
| EVAL_QUEUE_SORT | NOMAD::EvalSortType | QUADRATIC_MODEL | How to sort points before evaluation |
| PSD_MADS_SUBPROBLEM_MAX_BB_EVAL | size_t | INF | Max number of evaluations for each subproblem |
| SUBPROBLEM_MAX_BB_EVAL | size_t | INF | Internal parameter for PSD_MADS_SUBPROBLEM_MAX_BB_EVAL |
Evaluator Control Global Parameters (evaluatorControlGlobalAttributesDefinition.txt)
Total options in this section: 17
| Option | Type | Default | Short Description |
| --- | --- | --- | --- |
| BB_MAX_BLOCK_SIZE | size_t | 1 | Size of blocks of points, to be used for parallel evaluations |
| SURROGATE_MAX_BLOCK_SIZE | size_t | 1 | Size of blocks of points, to be used for parallel evaluations |
| EVAL_QUEUE_CLEAR | bool | true | Opportunistic strategy: Flag to clear EvaluatorControl queue between each run |
| EVAL_SURROGATE_COST | size_t | INF | Cost of the surrogate function versus the true function |
| MAX_BB_EVAL | size_t | INF | Stopping criterion on the number of blackbox evaluations |
| MAX_BLOCK_EVAL | size_t | INF | Stopping criterion on the number of blocks evaluations |
| MAX_EVAL | size_t | INF | Stopping criterion on the number of evaluations (blackbox and cache) |
| MAX_SURROGATE_EVAL_OPTIMIZATION | size_t | INF | Stopping criterion on the number of static surrogate evaluations |
| MODEL_MAX_BLOCK_SIZE | size_t | INF | Internal parameter for QUAD_MODEL_MAX_BLOCK_SIZE and SGTELIB_MODEL_MAX_BLOCK_SIZE |
| MODEL_MAX_EVAL | size_t | 1000 | Internal parameter for QUAD_MODEL_MAX_EVAL and SGTELIB_MODEL_MAX_EVAL |
| QUAD_MODEL_MAX_BLOCK_SIZE | size_t | INF | Size of blocks of points, to be used for parallel evaluations |
| QUAD_MODEL_MAX_EVAL | size_t | 2000 | Max number of model evaluations for optimization of the quad model problem |
| SGTELIB_MODEL_MAX_BLOCK_SIZE | size_t | INF | Size of blocks of points, to be used for parallel evaluations |
| SGTELIB_MODEL_MAX_EVAL | size_t | 2000 | Max number of model evaluations for each optimization of the sgtelib model problem |
| TMP_DIR | std::string | - | Directory where to put temporary files |
| USE_CACHE_FILE_FOR_RERUN | bool | false | Cache file for rerun |
| NB_THREADS_PARALLEL_EVAL | int | 1 | Max number of threads used for parallel evaluations of each algorithm |
Totals
- Total option entries across all definition files: 185
- To inspect option help at runtime:
snomadr(information = list("help" = "-h")) - To inspect a specific option at runtime:
snomadr(information = list("help" = "-h OPTION_NAME"))
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