uo.algorithm package

Subpackages

• uo.algorithm.exact package
  • Subpackages
    • uo.algorithm.exact.total_enumeration package
      • Submodules
      • uo.algorithm.exact.total_enumeration.problem_solution_te_support module
      • uo.algorithm.exact.total_enumeration.te_optimizer module
      • Module contents
  • Module contents
• uo.algorithm.metaheuristic package
  • Subpackages
    • uo.algorithm.metaheuristic.electro_magnetism_like_metaheuristic package
      • Module contents
    • uo.algorithm.metaheuristic.genetic_algorithm package
      • Module contents
    • uo.algorithm.metaheuristic.variable_neighborhood_search package
      • Submodules
      • uo.algorithm.metaheuristic.variable_neighborhood_search.problem_solution_vns_support module
      • uo.algorithm.metaheuristic.variable_neighborhood_search.vns_optimizer module
      • Module contents
  • Submodules
  • uo.algorithm.metaheuristic.metaheuristic module
    • Metaheuristic
      • Metaheuristic.additional_statistics_control
      • Metaheuristic.copy()
      • Metaheuristic.determine_fields_val()
      • Metaheuristic.elapsed_seconds()
      • Metaheuristic.finish_control
      • Metaheuristic.main_loop()
      • Metaheuristic.main_loop_iteration()
      • Metaheuristic.optimize()
      • Metaheuristic.random_seed
      • Metaheuristic.should_finish()
      • Metaheuristic.string_rep()
      • Metaheuristic.update_additional_statistics_if_required()
    • random()
    • SingleSolutionMetaheuristic
      • SingleSolutionMetaheuristic.copy()
      • SingleSolutionMetaheuristic.current_solution
      • SingleSolutionMetaheuristic.string_rep()
    • random()
    • PopulationBasedMetaheuristic
      • PopulationBasedMetaheuristic.copy()
      • PopulationBasedMetaheuristic.current_population
      • PopulationBasedMetaheuristic.string_rep()
    • random()
    • MetaheuristicVoid
      • MetaheuristicVoid.copy()
      • MetaheuristicVoid.init()
      • MetaheuristicVoid.main_loop_iteration()
    • random()
    • SingleSolutionMetaheuristicVoid
      • SingleSolutionMetaheuristicVoid.copy()
      • SingleSolutionMetaheuristicVoid.init()
      • SingleSolutionMetaheuristicVoid.main_loop_iteration()
    • random()
    • PopulationBasedMetaheuristicVoid
      • PopulationBasedMetaheuristicVoid.copy()
      • PopulationBasedMetaheuristicVoid.init()
      • PopulationBasedMetaheuristicVoid.main_loop_iteration()
    • random()
  • Module contents

Submodules

uo.algorithm.algorithm module

The algorithm module describes the class Algorithm.

class uo.algorithm.algorithm.Algorithm(problem: Problem, solution_template: Solution | None, name: str, output_control: OutputControl | None)

Bases: Optimizer

This class describes Algorithm.

name

The name of the algorithm.

Type:

str

output_control

The structure that controls output.

Type:

OutputControl

problem

The problem to be solved.

Type:

Problem

solution_template

The solution template for the problem to be solved.

Type:

Optional[Solution]

Properties:

solution_template (Optional[Solution]): The solution template for the problem to be solved. evaluation (int): The current number of evaluations during algorithm execution. iteration (int): The iteration of metaheuristic execution. iteration_best_found (int): The iteration when the best solution is found.

__init__(name

str, output_control: OutputControl, problem: Problem, solution_template: Optional[Solution] = None) -> None: Create a new Algorithm instance.

__copy__() → Algorithm

Internal copy of the current algorithm.

copy() → Algorithm

Copy the current algorithm.

init() → None

Initialization of the algorithm.

string_rep(delimiter

str, indentation: int = 0, indentation_symbol: str = ‘’, group_start: str = ‘{’, group_end: str = ‘}’) -> str: String representation of the ‘Algorithm’ instance.

__str__() → str

String representation of the ‘Algorithm’ instance.

__repr__() → str

Representation of the ‘Algorithm’ instance.

__format__(spec

str) -> str: Formatted ‘Algorithm’ instance.

property best_solution: Solution

Property getter for the best solution obtained during metaheuristic execution

Returns:

best solution so far

Return type:

Solution

abstract copy()

Copy the current algorithm

Returns:

new Algorithm instance with the same properties

Return type:

uo.algorithm.Algorithm

determine_fields_val(fields_def: list[str], fields_val: list[str]) → list[str]

Determines fields values upon fields definition and old values

Parameters:

• fields_def (list[str]) – list of field definitions

• fields_val (list[str]) – list of old field values

Returns:

list of new field values

Return type:

list[str]

property evaluation: int

Property getter for current number of evaluations during algorithm execution

Returns:

current number of evaluations

Return type:

int

property evaluation_best_found: int

Property getter for the evaluation when the best solution is found

Returns:

evaluation when the best solution is found

Return type:

int

property iteration: int

Property getter for the iteration of metaheuristic execution

Returns:

iteration

Return type:

int

property iteration_best_found: int

Property getter for the iteration when the best solution is found

Returns:

iteration when the best solution is found

Return type:

int

property solution_template: Solution | None

Property getter for the solution template for the problem to be solved

Returns:

solution template for the problem to be solved

Return type:

Solution

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

String representation of the ‘Algorithm’ 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

uo.algorithm.output_control module

The output_control module describes the class OutputControl.

class uo.algorithm.output_control.OutputControl(output_file: TextIOWrapper | None = None, fields: str = 'iteration, evaluation, "step_name", best_solution.string_representation(), best_solution.fitness_value, best_solution.objective_value, best_solution.is_feasible', moments: str = 'after_algorithm')

Bases: object

This class determine where the output generated during execution of the uo.algorithm.Algorithm instance will be written

copy()

Copy the current output control

Returns:

new OutputControl instance with the same properties

Return type:

OutputControl

property fields: str

Property getter for fields_definitions property

Returns:

comma-separated string with list of fields for output

Return type:

str

property fields_definitions: list[str]

Property getter for fields_definitions property

Returns:

list of fields definitions to be evaluated during output

Return type:

list[str]

property fields_headings: list[str]

Property getter for fields_headings property

Returns:

list of fields headings for output

Return type:

list[str]

property moments: str

Property getter for moments property

Returns:

comma-separated list of moments for output

Return type:

str

property output_file: TextIOWrapper

Property getter for output file

Returns:

output file to which algorithm will write

Return type:

TextIOWrapper

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

String representation of the target solution 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

property write_after_algorithm: bool

Property getter for property write_after_algorithm

Returns:

should write to the output after algorithm execution

Return type:

bool

property write_after_evaluation: bool

Property getter for property write_after_evaluation

Returns:

should write to the output after evaluation

Return type:

bool

property write_after_iteration: bool

Property getter for property write_after_iteration

Returns:

should write to the output after algorithm iteration

Return type:

bool

property write_after_step_in_iteration: bool

Property getter for property write_after_step_in_iteration

Returns:

should write to the output after step in iteration

Return type:

bool

property write_before_algorithm: bool

Property getter for property write_before_algorithm

Returns:

should write to the output prior to algorithm execution

Return type:

bool

property write_before_evaluation: bool

Property getter for property write_before_evaluation

Returns:

should write to the output prior to evaluation

Return type:

bool

property write_before_iteration: bool

Property getter for property write_before_iteration

Returns:

should write to the output prior to algorithm iteration

Return type:

bool

property write_before_step_in_iteration: bool

Property getter for property write_before_step_in_iteration

Returns:

should write to the output prior to step in iteration

Return type:

bool

Module contents