AL-SHADE

AL-SHADE (Adaptive L-SHADE with current-to-Amean strategy and adaptive mutation selection scheme)

class DETAlgs.al_shade.ALSHADE(params: ALSHADEData, db_conn=None, db_auto_write=False)[source]

Bases: BaseAlg

ALSHADE: A novel adaptive L-SHADE algorithm and its application in UAV swarm resource configuration problem

Links: https://www.sciencedirect.com/science/article/abs/pii/S0020025522004893

References: Li, Y., Han, T., Zhou, H., Tang, S., & Zhao, H. (2022). A novel adaptive L-SHADE algorithm and its application in UAV swarm resource configuration problem. Information Sciences, 606, 350–367. https://doi.org/10.1016/j.ins.2022.05.058

next_epoch()[source]

property nfe: int: Number of function evaluations performed so far.

run()

write_results_to_database(results_data)

class detpy.DETAlgs.data.alg_data.ALSHADEData(population_size: int = 100, max_nfe: int = 100000, dimension: int = 10, additional_stop_criteria: detpy.models.stop_condition.stop_condition.StopCondition = <detpy.models.stop_condition.never_stop_condition.NeverStopCondition object at 0x7f136577ee40>, lb: list = <factory>, ub: list = <factory>, optimization_type: detpy.models.enums.optimization.OptimizationType = <OptimizationType.MINIMIZATION: 'minimization'>, boundary_constraints_fun: detpy.models.enums.boundary_constrain.BoundaryFixing = <BoundaryFixing.RANDOM: 'random'>, function: detpy.models.fitness_function.FitnessFunctionBase = None, log_population: bool = False, parallel_processing: Optional[list] = None, show_plots: bool = True, minimum_population_size: int = 4, memory_size: int = 6, archive_size: int = 100, elite_factor: float = 0.5, init_probability_mutation_strategy: float = 0.5, population_size_reduction_strategy: detpy.DETAlgs.population_reduction.population_size_reduction_strategy.PopulationSizeReductionStrategy = <detpy.DETAlgs.population_reduction.linear_population_size_reduction.LinearPopulationSizeReduction object at 0x7f136519f650>)[source]

Bases: BaseData

additional_stop_criteria: StopCondition = <detpy.models.stop_condition.never_stop_condition.NeverStopCondition object>

archive_size: int = 100

boundary_constraints_fun: BoundaryFixing = 'random'

dimension: int = 10

elite_factor: float = 0.5

function: FitnessFunctionBase = None

init_probability_mutation_strategy: float = 0.5

lb: list

log_population: bool = False

max_nfe: int = 100000

memory_size: int = 6

minimum_population_size: int = 4

optimization_type: OptimizationType = 'minimization'

parallel_processing: list | None = None

population_size: int = 100

population_size_reduction_strategy: PopulationSizeReductionStrategy = <detpy.DETAlgs.population_reduction.linear_population_size_reduction.LinearPopulationSizeReduction object>

show_plots: bool = True

ub: list