evomo.problems.constrained.base

Classes

CMOP	Base class for Constrained Multi-objective Optimization Problems (CMOP).

Functions

default_shape(→ Dict[str, Tuple[int, ...]])

Module Contents

evomo.problems.constrained.base.default_shape(problem, n: int) → Dict[str, Tuple[int, ...]]

class evomo.problems.constrained.base.CMOP(d: int, m: int, n_iq: int, n_eq: int, lb: torch.Tensor, ub: torch.Tensor, *, scale_d: bool = False, constr_eq_eps: float = 0.0001, return_cv: bool = False, requires_kwargs: bool = False, callback=None, device: torch.device | None = None, dtype: torch.dtype | None = None)

Bases: evox.core.Problem

Base class for Constrained Multi-objective Optimization Problems (CMOP).

device

dtype

d

m

n_iq

n_eq

n_constraints

constr_eq_eps = 0.0001

dim

lb

ub

scale_d = False

return_cv = False

requires_kwargs = False

callback = None

name() → str

has_bounds() → bool

has_constraints() → bool

bounds() → Tuple[torch.Tensor, torch.Tensor]

evaluate(X: torch.Tensor)

Evaluate the population X. Returns a tuple (fitness, constraint_violation).

abstractmethod fn(X: torch.Tensor) → torch.Tensor

abstractmethod pf()