pymead.optimization.opt_setup.TPAIOPT#
- class TPAIOPT(n_var: int, n_obj: int, n_constr: int, xl: int, xu: int, param_dict: dict)[source]#
Bases:
PymeadGAProblem- __init__(n_var: int, n_obj: int, n_constr: int, xl: int, xu: int, param_dict: dict)#
Simple problem statement for the
pymoopackage.- Parameters:
n_var (int) – Number of design variables (equal to the length of the normalized paramter list)
n_obj (int) – Number of objectives
n_constr (int) – Number of constraints
xl (int or list or np.ndarray) – Lower bounds for the parameters. If
int, all lower bounds are equal.xu (int or list or np.ndarray) – Upper bounds for the parameters. If
int, all lower bounds are equal.param_dict (dict) – Parameter dictionary used for the shape optimization.
Methods