uo.algorithm.metaheuristic.monte_carlo package

Submodules

uo.algorithm.metaheuristic.monte_carlo.monte_carlo_optimizer module

The variable_neighborhood_search contains class MonteCarloOptimizer, that represents implements algorithm MonteCarlo.

class uo.algorithm.metaheuristic.monte_carlo.monte_carlo_optimizer.MonteCarloOptimizer(finish_control: FinishControl, problem: Problem, solution_template: Solution | None, output_control: OutputControl | None = None, random_seed: int | None = None, additional_statistics_control: AdditionalStatisticsControl | None = None)

Bases: SingleSolutionMetaheuristic

Instance of the class MonteCarloOptimizer encapsulate Variable Neighborhood Search optimization algorithm.

copy()

Internal copy of the current instance

Returns:

new instance with the same properties

classmethod from_construction_tuple(construction_tuple: MonteCarloOptimizerConstructionParameters)

Additional constructor, that creates new instance of class MonteCarloOptimizer.

Parameters:

construction_tuple (MonteCarloOptimizerConstructionParameters) – tuple with all constructor parameters

init() → None

Initialization of the MonteCarlo algorithm

main_loop_iteration() → None

One iteration within main loop of the MonteCarlo algorithm

string_rep(delimiter: str, indentation: int = 0, indentation_symbol: str = '', group_start: str = '{', group_end: str = '}') → str

String representation of the MonteCarloOptimizer instance

Parameters:

  • delimiter (str) – delimiter between fields

  • indentation (int, optional, default value 0) – level of indentation

  • indentation_symbol (str, optional, default value '') – indentation symbol

  • group_start (str, optional, default value '{') – group start string

  • group_end (str, optional, default value '}') – group end string

Returns:

string representation of instance that controls output

Return type:

str

<<<<<<< HEAD class uo.algorithm.metaheuristic.monte_carlo.monte_carlo_optimizer.MonteCarloOptimizerConstructionParameters(finish_control: FinishControl | None = None, problem: Problem = None, solution_template: Solution | None = None, output_control: OutputControl | None = None, random_seed: int | None = None, additional_statistics_control: AdditionalStatisticsControl | None = None)
======= class uo.algorithm.metaheuristic.monte_carlo.monte_carlo_optimizer.MonteCarloOptimizerConstructionParameters(finish_control: FinishControl | None = None, problem: Problem | None = None, solution_template: Solution | None = None, output_control: OutputControl | None = None, random_seed: int | None = None, additional_statistics_control: AdditionalStatisticsControl | None = None) >>>>>>> origin/develop

Bases: object

Instance of the class MonteCarloOptimizerConstructionParameters represents constructor parameters for Monte Carlo algorithm.

additional_statistics_control: AdditionalStatisticsControl | None = None
finish_control: FinishControl | None = None
output_control: OutputControl | None = None
problem: Problem = None
random_seed: int | None = None
solution_template: Solution | None = None
uo.algorithm.metaheuristic.monte_carlo.monte_carlo_optimizer.random() → x in the interval [0, 1).

uo.algorithm.metaheuristic.monte_carlo.test_monte_carlo_optimizer module

class uo.algorithm.metaheuristic.monte_carlo.test_monte_carlo_optimizer.TestMonteCarloOptimizer(methodName='runTest')

Bases: TestCase

test_from_construction_tuple()
test_init_method_initializes_solutions()
test_initialization_with_valid_parameters()
test_invalid_parameter_types_in_constructor()
test_main_loop_iteration_no_improvement()
test_problem_not_properly_defined()
test_random_seed_affects_randomness()
test_string_representation()

Module contents