simopt.solvers.randomsearch
===========================

.. py:module:: simopt.solvers.randomsearch

.. autoapi-nested-parse::

   Random Search Solver.

   Randomly sample solutions from the feasible region.
   Can handle stochastic constraints.
   A detailed description of the solver can be found `here <https://simopt.readthedocs.io/en/latest/randomsearch.html>`__.





Module Contents
---------------

.. py:class:: RandomSearchConfig

   Bases: :py:obj:`simopt.base.SolverConfig`


   Configuration for Random Search solver.


   .. py:attribute:: sample_size
      :type:  Annotated[int, Field(default=10, gt=0, description='sample size per solution')]


.. py:class:: RandomSearch(name: str = '', fixed_factors: dict | None = None)

   Bases: :py:obj:`simopt.base.Solver`


   Random Search Solver.

   A solver that randomly samples solutions from the feasible region.
   Take a fixed number of replications at each solution.

   Initialize a solver object.

   :param name: Name of the solver. Defaults to an empty string.
   :type name: str, optional
   :param fixed_factors: Dictionary of user-specified solver
                         factors. Defaults to None.
   :type fixed_factors: dict | None, optional


   .. py:attribute:: name
      :type:  str
      :value: 'RNDSRCH'



   .. py:attribute:: config_class
      :type:  ClassVar[type[simopt.base.SolverConfig]]

      Configuration class for the solver.


   .. py:attribute:: class_name_abbr
      :type:  ClassVar[str]
      :value: 'RNDSRCH'


      Short name of the solver class.


   .. py:attribute:: class_name
      :type:  ClassVar[str]
      :value: 'Random Search'


      Long name of the solver class.


   .. py:attribute:: objective_type
      :type:  ClassVar[simopt.base.ObjectiveType]

      Description of objective types.


   .. py:attribute:: constraint_type
      :type:  ClassVar[simopt.base.ConstraintType]

      Description of constraint types.


   .. py:attribute:: variable_type
      :type:  ClassVar[simopt.base.VariableType]

      Description of variable types.


   .. py:attribute:: gradient_needed
      :type:  ClassVar[bool]
      :value: False


      True if gradient of objective function is needed, otherwise False.


   .. py:method:: solve(problem: simopt.base.Problem) -> None

      Run a single macroreplication of a solver on a problem.

      :param problem: Simulation-optimization problem to solve.
      :type problem: Problem

      :returns:     - list [Solution]: List of solutions recommended throughout the budget.
                    - list [int]: List of intermediate budgets when recommended solutions
                        change.
      :rtype: tuple