Guide to build Matlab interface for Windows using MinGW

The following guide for building Matlab interface for Windows using MinGW has been provided by a user in GitHub Issue #128.

* Update MATLAB’s MinGW using this link to supported compilers. Follow on-screen instructions (for example, dragging and dropping in MATLAB’s command window) NB: Updates will be displayed in MATLAB’s Command window while installation is in progress.

* Confirm set up by typing mex -setup in command window to verify installation following completion (Please check MATLAB and Simulink requirements on the same page using the link above as well)

* Majority of the other installation procedures would be done using “Command Prompt Window”. This can easily be accessed by typing “Command window” in the search tile on your Windows operating system.

* Download CMake. I recommend using the Windows x64 Installer option to enable you make your own installation settings. Make sure it is available for all users of the PC. Confirm that cmake is on the PC by typing cmake on command prompt.

* Download your preferred NOMAD version and unzip the file. In the root folder, get a link which is done by easily double-clicking on the pane which bears the opened folder.

* The interface build is managed by CMake that can be run at NOMAD root. Use the command cd copiedAddress command in command prompt to change the directory to the location you have copied above (replace copiedAddress with the link obtained)

* To build the MATLAB interface, force the use of the 64bit version of the compiler with the command:

cmake -DTEST_OPENMP=OFF -DBUILD_INTERFACE_MATLAB=ON -S . -B build/release -A x64

* Following the completion, use the command below that might take some minutes:

cmake --build build/release --config Release

* Then, finally, use the command:

cmake --install build/release

which must be run before using the Matlab nomadOpt function. You can expect to see the following during the build process:

* Make sure to add NOMAD subfolders on MATLAB before testing the installation. On MATLAB’s Home, use the “Set Path” menu to “Add with Subfolders” the whole NOMAD folder so that functions can easily be accessed

* Run examples provided in the installation folder to confirm that the functions can now be called easily from MATLAB’s command window. For example, trying to solve problem three (3) should give you something similar to:

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.

NOMAD 4 parameters

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
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
BB_REDIRECTION	bool	basic	Blackbox executable redirection for outputs	true
CACHE_FILE	std::string	basic	Cache file name
CACHE_SIZE_MAX	size_t	advanced	Maximum number of evaluation points to be stored in the cache	INF
CS_OPTIMIZATION	bool	basic	Coordinate Search optimization	false
DIMENSION	size_t	basic	Dimension of the optimization problem (required)	0
DIRECTION_TYPE	NOMAD::DirectionTypeList	advanced	Direction types for Poll steps	ORTHO N+1 QUAD
DIRECTION_TYPE_SECONDARY_POLL	NOMAD::DirectionTypeList	advanced	Direction types for Mads secondary poll	DOUBLE
DISCO_MADS_DETECTION_RADIUS	NOMAD::Double	advanced	Radius used to reveal discontinuities in DiscoMads	1.0
DISCO_MADS_EXCLUSION_RADIUS	NOMAD::Double	advanced	Radius of exclusion balls around revealing points in DiscoMads	1
DISCO_MADS_LIMIT_RATE	NOMAD::Double	advanced	Limit rate of change used to reveal discontinuities in DiscoMads	1
DISCO_MADS_REVEALING_POLL_NB_POINTS	size_t	advanced	Number of random points sampled by the revealing poll in DiscoMads	1
DISCO_MADS_REVEALING_POLL_RADIUS	NOMAD::Double	advanced	Revealing poll radius in DiscoMads	2.02
DISPLAY_ALL_EVAL	bool	basic	Flag to display all evaluations	false
DISPLAY_DEGREE	int	basic	Level of verbose during execution	2
DISPLAY_FAILED	bool	advanced	Flag to display failed evaluation	false
DISPLAY_HEADER	size_t	advanced	Frequency at which the stats header is displayed	40
DISPLAY_INFEASIBLE	bool	advanced	Flag to display infeasible	true
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	false
DMULTIMADS_OPTIMIZATION	bool	advanced	DMultiMads solves multiobjective optimization problems	false
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	QUADRATIC_MODEL
EVAL_STATS_FILE	string	basic	The name of the file for stats about evaluations and successes
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
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
HISTORY_FILE	std::string	basic	The name of the history file
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
H_MAX_0	NOMAD::Double	advanced	Initial value of hMax.	NOMAD::INF
INITIAL_FRAME_SIZE	NOMAD::ArrayOfDouble	advanced	The initial frame size of MADS
INITIAL_MESH_SIZE	NOMAD::ArrayOfDouble	advanced	The initial mesh size of MADS
LH_EVAL	size_t	basic	Latin Hypercube Sampling of points (no optimization)	0
LH_SEARCH	NOMAD::LHSearchType	basic	Latin Hypercube Sampling Search method
LOWER_BOUND	NOMAD::ArrayOfDouble	basic	The optimization problem lower bounds for each variable
MAX_BB_EVAL	size_t	basic	Stopping criterion on the number of blackbox evaluations	INF
MAX_EVAL	size_t	advanced	Stopping criterion on the number of evaluations (blackbox and cache)	INF
MAX_ITERATIONS	size_t	advanced	The maximum number of iterations of the MADS algorithm	INF
MAX_ITERATION_PER_MEGAITERATION	size_t	advanced	Maximum number of Iterations to generate for each MegaIteration.	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	advanced	Termination criterion on minimal frame size of MADS
MIN_MESH_SIZE	NOMAD::ArrayOfDouble	advanced	Termination criterion on minimal mesh size of MADS
NB_THREADS_OPENMP	int	advanced	The number of threads when OpenMP parallel evaluations are enabled	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
ORTHO_MESH_REFINE_FREQ	size_t	advanced	Control mesh refinement frequency	1
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
QP_ABSOLUTETOL	NOMAD::Double	advanced	A quad model based search step for Mads using a QP solver	1e-3
QP_AUGLAG_ETA0	NOMAD::Double	advanced	A quad model based search step for Mads using a QP solver	1.0
QP_AUGLAG_MAXITERINNER	size_t	advanced	A quad model based search step for Mads using a QP solver	10
QP_AUGLAG_MAXSUCCESSIVFAIL	size_t	advanced	A quad model based search step for Mads using a QP solver	3
QP_AUGLAG_MU0	NOMAD::Double	advanced	A quad model based search step for Mads using a QP solver	0.5
QP_AUGLAG_MUDECREASE	NOMAD::Double	advanced	A quad model based search step for Mads using a QP solver	2
QP_AUGLAG_OMEGA0	NOMAD::Double	advanced	A quad model based search step for Mads using a QP solver	1.0
QP_AUGLAG_SUCCESSRATIO	NOMAD::Double	advanced	A quad model based search step for Mads using a QP solver	0.99
QP_AUGLAG_TOLDISTDXINNER	NOMAD::Double	advanced	A quad model based search step for Mads using a QP solver	1e-15
QP_MAXITER	size_t	advanced	A quad model based search step for Mads using a QP solver	10
QP_OPTIMIZATION	bool	advanced	Quad model stand alone QP optimization for constrained and unconstrained pbs	false
QP_RELATIVETOL	NOMAD::Double	advanced	A quad model based search step for Mads using a QP solver	1e-3
QP_SEARCH	bool	advanced	A quad model based search step for Mads using a QP solver	false
QP_SELECTALGO	size_t	advanced	Select the algorithm for QP solver	0
QP_TOLCOND	NOMAD::Double	advanced	A quad model based search step for Mads using a QP solver	1e-15
QP_TOLDISTDX	NOMAD::Double	advanced	A quad model based search step for Mads using a QP solver	-1.0
QP_TOLMESH	NOMAD::Double	advanced	A quad model based search step for Mads using a QP solver	1.0
QP_VERBOSE	bool	advanced	A quad model based search step for Mads using a QP solver	false
QP_VERBOSEFULL	bool	advanced	A quad model based search step for Mads using a QP solver	false
QUAD_MODEL_AND_LH_SEARCH	bool	basic	Quad model and LH search	false
QUAD_MODEL_DISPLAY	std::string	advanced	Display of a model
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 optimization of the quad model problem	2000
QUAD_MODEL_OPTIMIZATION	bool	advanced	Quad model stand alone optimization for constrained and unconstrained pbs	false
QUAD_MODEL_SEARCH	bool	basic	Quad model search	true
QUAD_MODEL_SLD_SEARCH	bool	basic	Quad model (SLD) search	false
RANDOM_ALGO_DUMMY_FACTOR	size_t	advanced	Dummy factor for random algo (used as template)	1
RANDOM_ALGO_OPTIMIZATION	bool	advanced	A standalone random optimization algo (several iterations)	false
RANDOM_ALGO_SEARCH	bool	advanced	A random search step for Mads using an algo (several iterations)	false
RANDOM_SIMPLE_SEARCH	bool	advanced	A template for a simple (no iteration) random search step for Mads	false
REJECT_UNKNOWN_PARAMETERS	bool	advanced	Flag to reject unknown parameters when checking validity of parameters	true
RHO	NOMAD::Double	advanced	Rho parameter of the progressive barrier	0.1
SEARCH_METHOD_MESH_PROJECTION	bool	advanced	Projection on mesh for trial points from a search method	true
SEED	int	advanced	The seed for the pseudo-random number generator	0
SET_FILE	bool	advanced	Boolean to determine if the file of the set is already created	false
SET_FILE_NAME	string	advanced	File to load with the set
SGTELIB_MAX_POINTS_FOR_MODEL	size_t	advanced	Maximum number of valid points used to build a model	500
SGTELIB_MIN_POINTS_FOR_MODEL	size_t	advanced	Minimum number of valid points necessary to build a model	1
SGTELIB_MODEL_DEFINITION	NOMAD::ArrayOfString	advanced	Definition of the Sgtelib model
SGTELIB_MODEL_DISPLAY	std::string	advanced	Display of a model
SGTELIB_MODEL_DIVERSIFICATION	NOMAD::Double	advanced	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	advanced	Method used to model the feasibility of a point	C
SGTELIB_MODEL_FORMULATION	NOMAD::SgtelibModelFormulationType	advanced	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	2000
SGTELIB_MODEL_SEARCH	bool	basic	Model search using Sgtelib	false
SGTELIB_MODEL_SEARCH_CANDIDATES_NB	int	advanced	Number of candidates returned by the sgtelib model search	-1
SGTELIB_MODEL_SEARCH_EXCLUSION_AREA	NOMAD::Double	advanced	Exclusion area for the sgtelib model search around points of the cache	0.0
SGTELIB_MODEL_SEARCH_FILTER	std::string	advanced	Methods used in the sgtelib search filter to return several search candidates	2345
SIMPLE_LINE_SEARCH	bool	basic	MADS simple line search method complement speculative search	false
SOLUTION_FILE	std::string	basic	The name of the file containing the best feasible solution
SOLUTION_FILE_FINAL	bool	basic	Flag to decide when to write best feasible solution	false
SPECULATIVE_SEARCH	bool	basic	MADS speculative search method	true
SPECULATIVE_SEARCH_BASE_FACTOR	NOMAD::Double	advanced	Distance of the MADS speculative search method	4.0
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
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
SURROGATE_MAX_BLOCK_SIZE	size_t	advanced	Size of blocks of points, to be used for parallel evaluations	1
SYSTEM_FILE_NAME	string	advanced	File with the constraints
TMP_DIR	std::string	advanced	Directory where to put temporary files
TRIAL_POINT_MAX_ADD_UP	size_t	advanced	Max number of trial points	0
UPPER_BOUND	NOMAD::ArrayOfDouble	basic	The optimization problem upper bounds for each variable
USER_CALLS_ENABLED	bool	advanced	Controls the automatic calls to user function	true
USE_CACHE_FILE_FOR_RERUN	bool	advanced	Cache file for rerun	false
USE_IBEX	bool	advanced	Boolean to determine if we want to use the functionnalities of IBEX	false
VARIABLE_GROUP	NOMAD::ListOfVariableGroup	advanced	The groups of variables)
VNSMART_MADS_SEARCH	bool	advanced	VNS Mads search under condition of consecutive fails	false
VNSMART_MADS_SEARCH_THRESHOLD	int	advanced	Threshold for VNS (SMART) Mads search	3
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
VNS_MADS_SEARCH_WITH_SURROGATE	bool	advanced	VNS Mads search with surrogate	false
X0	NOMAD::ArrayOfPoint	basic	The initial point(s)