desdeo.optimization.OptimizationMethod

This module contains methods for solving single-objective optimization problems.

class desdeo.optimization.OptimizationMethod.OptimalSearch(optimization_problem)

Bases: desdeo.optimization.OptimizationMethod.OptimizationMethod

Abstract class for optimal search

__abstractmethods__ = frozenset({'_objective', '_search'})

__module__ = 'desdeo.optimization.OptimizationMethod'

class desdeo.optimization.OptimizationMethod.OptimizationMethod(optimization_problem)

Bases: object

Abstract class for optimization methods

_max

True if the objective function is to be maximized

Type

bool (default:False)

_ceoff

Coefficient for the objective function

Type

float

__abstractmethods__ = frozenset({'_search'})

__dict__ = mappingproxy({'__module__': 'desdeo.optimization.OptimizationMethod', '__doc__': '\n Abstract class for optimization methods\n\n Attributes\n ----------\n _max : bool (default:False)\n True if the objective function is to be maximized\n\n _ceoff : float\n Coefficient for the objective function\n ', '__init__': <function OptimizationMethod.__init__>, 'search': <function OptimizationMethod.search>, '_search': <function OptimizationMethod._search>, '__dict__': <attribute '__dict__' of 'OptimizationMethod' objects>, '__weakref__': <attribute '__weakref__' of 'OptimizationMethod' objects>, '__abstractmethods__': frozenset({'_search'}), '_abc_registry': <_weakrefset.WeakSet object>, '_abc_cache': <_weakrefset.WeakSet object>, '_abc_negative_cache': <_weakrefset.WeakSet object>, '_abc_negative_cache_version': 42})

__init__(optimization_problem)

Initialize self. See help(type(self)) for accurate signature.

__module__ = 'desdeo.optimization.OptimizationMethod'

__weakref__

list of weak references to the object (if defined)

search(max=False, **params)

Search for the optimal solution

This sets up the search for the optimization and calls the _search method

Parameters

• max (bool (default False)) – If true find mximum of the objective function instead of minimum

• **params (dict [optional]) – Parameters for single objective optimization method

Return type

Tuple[numpy.ndarray, List[float]]

class desdeo.optimization.OptimizationMethod.PointSearch(optimization_problem)

Bases: desdeo.optimization.OptimizationMethod.OptimizationMethod

__abstractmethods__ = frozenset({})

__module__ = 'desdeo.optimization.OptimizationMethod'

class desdeo.optimization.OptimizationMethod.SciPy(optimization_problem)

Bases: desdeo.optimization.OptimizationMethod.OptimalSearch

__abstractmethods__ = frozenset({})

__module__ = 'desdeo.optimization.OptimizationMethod'

class desdeo.optimization.OptimizationMethod.SciPyDE(optimization_problem)

Bases: desdeo.optimization.OptimizationMethod.OptimalSearch

__abstractmethods__ = frozenset({})

__init__(optimization_problem)

Initialize self. See help(type(self)) for accurate signature.

__module__ = 'desdeo.optimization.OptimizationMethod'