FIADE

FIADE (Fitness-Adaptive DE) [

class DETAlgs.fiade.FiADE(params: FiADEData, db_conn=None, db_auto_write=False)[source]

Bases: BaseAlg

Links: https://www.sciencedirect.com/science/article/abs/pii/S0020025511001381

References: Arnob Ghosh , Swagatam Das , Aritra Chowdhury , Ritwik Giri (2011) An Improved Differential Evolution Algorithm with Fitness-Based Adaptation of the Control Parameters. Volume 181, Issue 18, 15 September 2011, Pages 3749-3765 doi: 10.1016/j.ins.2011.03.010

next_epoch()[source]

run()

write_results_to_database(results_data)

class detpy.DETAlgs.data.alg_data.FiADEData(epoch: int = 100, population_size: int = 100, dimension: int = 10, lb: list = <factory>, ub: list = <factory>, mode: 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, mutation_factor: float = 0.5, crossover_rate: float = 0.5, adaptive: bool = True)[source]

Bases: BaseData

adaptive: bool = True

boundary_constraints_fun: BoundaryFixing = 'random'

crossover_rate: float = 0.5

dimension: int = 10

epoch: int = 100

function: FitnessFunctionBase = None

lb: list

log_population: bool = False

mode: OptimizationType = 'minimization'

mutation_factor: float = 0.5

parallel_processing: list | None = None

population_size: int = 100

ub: list