Optimization algorithms

In this example, we will discover the different functions of the API related to optimization algorithms.

from __future__ import absolute_import, division, print_function, unicode_literals

from future import standard_library

from gemseo.api import (



Get available optimization algorithms

The get_available_opt_algorithms() function returns the list of optimization algorithms available in GEMSEO or in external modules




Get options schema

For a given optimization algorithm, e.g. "NLOPT_SLSQP", we can get the options; e.g.



{'name': 'NLOPT_options', '$schema': 'http://json-schema.org/draft-04/schema', 'type': 'object', 'properties': {'xtol_rel': {'minimum': 0.0, 'type': 'number', 'description': 'Relative design parameter tolerance\n:type xtol_rel: float\n'}, 'normalize_design_space': {'type': 'boolean', 'description': 'If True, scales variables in [0, 1]\n:type normalize_design_space: bool\n'}, 'xtol_abs': {'minimum': 0.0, 'type': 'number', 'description': 'Design parameter tolerance\n:type xtol_abs: float\n'}, 'ftol_rel': {'minimum': 0.0, 'type': 'number', 'description': 'Relative objective function tolerance\n:type ftol_rel: float\n'}, 'ftol_abs': {'minimum': 0.0, 'type': 'number', 'description': 'Objective function tolerance\n:type ftol_abs: float\n'}, 'max_iter': {'minimum': 1, 'type': 'integer', 'description': 'maximum number of iterations\n:type max_iter: int\n'}, 'max_time': {'minimum': 0.0, 'type': 'number', 'description': 'Maximum time\n:type max_time: float\n'}, 'stopval': {'type': 'number', 'description': 'Stop when an objective value of at least stopval\nis found:\nstop minimizing when an objective value :math:`\\leq` stopval is\nfound,\nor stop maximizing a value :math:`\\geq` stopval is found.\n:type stopval: float\n'}, 'ctol_abs': {'minimum': 0.0, 'type': 'number', 'description': 'Absolute tolerance for constraints\n:type ctol_abs: float\n'}, 'eq_tolerance': {'minimum': 0.0, 'type': 'number', 'description': 'equality tolerance\n:type eq_tolerance: float\n'}, 'ineq_tolerance': {'minimum': 0.0, 'type': 'number', 'description': 'inequality tolerance\n:type ineq_tolerance: float\n'}, 'init_step': {'minimum': 0.0, 'type': 'number', 'description': 'initial step size for derivavtive free algorithms\nincreasing init_step will make the initial DOE in COBYLA\nwider steps in the design variables. By defaults, each variable\nis set to x0 + a perturbation that worths 0.25*(ub_i-x0_i) for i\nin xrange(len(x0))\n:type init_step: float'}}, 'required': ['max_iter']}

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