evomo.problems.constrained.doc

Classes

DOC1
DOC2
DOC3
DOC4
DOC5
DOC6
DOC7
DOC8
DOC9

Module Contents

class evomo.problems.constrained.doc.DOC1(ref_num: int = 1000, **kwargs)

Bases: evomo.problems.constrained.base.CMOP

Z. Liu and Y. Wang, Handling constrained multiobjective optimization problems with constraints in both the decision and objective spaces. IEEE Transactions on Evolutionary Computation, 2019, 23(5): 870-884.

m = 2

d = 6

lower

upper

ref_num = 1000

fn(X: torch.Tensor) → torch.Tensor

pf()

class evomo.problems.constrained.doc.DOC2(ref_num: int = 1000, **kwargs)

Bases: evomo.problems.constrained.base.CMOP

m = 2

d = 16

lower

upper

ref_num = 1000

fn(X: torch.Tensor) → torch.Tensor

pf()

class evomo.problems.constrained.doc.DOC3(ref_num: int = 1000, **kwargs)

Bases: evomo.problems.constrained.base.CMOP

m = 2

d = 10

lower

upper

ref_num = 1000

fn(X: torch.Tensor) → torch.Tensor

pf()

class evomo.problems.constrained.doc.DOC4(ref_num: int = 1000, **kwargs)

Bases: evomo.problems.constrained.base.CMOP

m = 2

d = 8

lower

upper

ref_num = 1000

fn(X: torch.Tensor) → torch.Tensor

pf()

class evomo.problems.constrained.doc.DOC5(ref_num: int = 1000, **kwargs)

Bases: evomo.problems.constrained.base.CMOP

m = 2

d = 8

lower

upper

ref_num = 1000

fn(X: torch.Tensor) → torch.Tensor

pf()

class evomo.problems.constrained.doc.DOC6(ref_num: int = 1000, **kwargs)

Bases: evomo.problems.constrained.base.CMOP

m = 2

d = 11

lower

upper

ref_num = 1000

fn(X: torch.Tensor) → torch.Tensor

pf()

class evomo.problems.constrained.doc.DOC7(ref_num: int = 1000, **kwargs)

Bases: evomo.problems.constrained.base.CMOP

m = 2

d = 11

lower

upper

ref_num = 1000

fn(X: torch.Tensor) → torch.Tensor

pf()

class evomo.problems.constrained.doc.DOC8(ref_num: int = 1000, **kwargs)

Bases: evomo.problems.constrained.base.CMOP

m = 3

d = 10

lower

upper

ref_num = 1000

fn(X: torch.Tensor) → torch.Tensor

pf()

class evomo.problems.constrained.doc.DOC9(ref_num: int = 1000, **kwargs)

Bases: evomo.problems.constrained.base.CMOP

m = 3

d = 11

lower

upper

ref_num = 1000

fn(X: torch.Tensor) → torch.Tensor

pf()