piglot.optimisers.aoa.AOA
- class AOA(objective: Objective, n_solutions=10, alpha=5.0, mu=0.5, epsilon=1e-12, seed=1, MOA_start=0.2, MOA_end=1.0)[source]
Bases:
ScalarOptimiserAOA optimiser. Documentation: https://www.sciencedirect.com/science/article/pii/S0045782520307945
Attributes
- n_solutionsinteger
population size (number of candidate solutions)
- alphafloat
non-negative sensitive parameter used to define the accuracy of the exploitation over the iterations
- mufloat
non-negative control parameter to adjust the search process
- epsilonfloat
small number to avoid division by zero
- seedint
random state seed
- MOA_startfloat
Math Optimizer Accelerated function initial value
- MOA_endfloat
Math Optimizer Accelerated function end value
Methods
- _optimise(self, func, n_dim, n_iter, bound, init_shot):
Solves the optimization problem
Methods
Optimiser for the outside world.
- optimise(n_iter: int, parameters: ~piglot.parameter.ParameterSet, output_dir: str, stop_criteria: ~piglot.optimiser.StoppingCriteria = <piglot.optimiser.StoppingCriteria object>, verbose: bool = True) Tuple[float, ndarray]
Optimiser for the outside world.
Parameters
- objectiveObjective
Objective function to optimise.
- n_iterint
Maximum number of iterations.
- parametersParameterSet
Set of parameters to optimise.
- output_dirstr
Whether to write output to the output directory, by default None.
- stop_criteriaStoppingCriteria
List of stopping criteria, by default none attributed.
- verbosebool
Whether to output progress status, by default True.
Returns
- float
Best observed objective value.
- np.ndarray
Observed optimum of the objective.