evomo.problems.numerical.wfg

Classes

WFG	Base class for the Walking Fish Group benchmark problems.
WFG1	Base class for the Walking Fish Group benchmark problems.
WFG2	Base class for the Walking Fish Group benchmark problems.
WFG3	Base class for the Walking Fish Group benchmark problems.
WFG4	Base class for the Walking Fish Group benchmark problems.
WFG5	Base class for the Walking Fish Group benchmark problems.
WFG6	Base class for the Walking Fish Group benchmark problems.
WFG7	Base class for the Walking Fish Group benchmark problems.
WFG8	Base class for the Walking Fish Group benchmark problems.
WFG9	Base class for the Walking Fish Group benchmark problems.

Module Contents

class evomo.problems.numerical.wfg.WFG(d: int | None = None, m: int = 3, ref_num: int = 1000, k: int | None = None)

Bases: evox.core.Problem

Base class for the Walking Fish Group benchmark problems.

Decision variables follow the PlatEMO scale: lower = 0 and upper = [2, 4, ..., 2*d]. The position parameter k defaults to m - 1 and should be a multiple of m - 1.

m = 3

k = 2

d = 12

ref_num = 1000

lower

upper

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

pf() → torch.Tensor

class evomo.problems.numerical.wfg.WFG1(d: int | None = None, m: int = 3, ref_num: int = 1000, k: int | None = None)

Bases: WFG

Base class for the Walking Fish Group benchmark problems.

Decision variables follow the PlatEMO scale: lower = 0 and upper = [2, 4, ..., 2*d]. The position parameter k defaults to m - 1 and should be a multiple of m - 1.

evaluate(X: torch.Tensor) → torch.Tensor

pf() → torch.Tensor

class evomo.problems.numerical.wfg.WFG2(d: int | None = None, m: int = 3, ref_num: int = 1000, k: int | None = None)

Bases: WFG

Base class for the Walking Fish Group benchmark problems.

Decision variables follow the PlatEMO scale: lower = 0 and upper = [2, 4, ..., 2*d]. The position parameter k defaults to m - 1 and should be a multiple of m - 1.

evaluate(X: torch.Tensor) → torch.Tensor

pf() → torch.Tensor

class evomo.problems.numerical.wfg.WFG3(d: int | None = None, m: int = 3, ref_num: int = 1000, k: int | None = None)

Bases: WFG2

Base class for the Walking Fish Group benchmark problems.

Decision variables follow the PlatEMO scale: lower = 0 and upper = [2, 4, ..., 2*d]. The position parameter k defaults to m - 1 and should be a multiple of m - 1.

evaluate(X: torch.Tensor) → torch.Tensor

pf() → torch.Tensor

class evomo.problems.numerical.wfg.WFG4(d: int | None = None, m: int = 3, ref_num: int = 1000, k: int | None = None)

Bases: WFG

Base class for the Walking Fish Group benchmark problems.

Decision variables follow the PlatEMO scale: lower = 0 and upper = [2, 4, ..., 2*d]. The position parameter k defaults to m - 1 and should be a multiple of m - 1.

evaluate(X: torch.Tensor) → torch.Tensor

class evomo.problems.numerical.wfg.WFG5(d: int | None = None, m: int = 3, ref_num: int = 1000, k: int | None = None)

Bases: WFG

Base class for the Walking Fish Group benchmark problems.

Decision variables follow the PlatEMO scale: lower = 0 and upper = [2, 4, ..., 2*d]. The position parameter k defaults to m - 1 and should be a multiple of m - 1.

evaluate(X: torch.Tensor) → torch.Tensor

class evomo.problems.numerical.wfg.WFG6(d: int | None = None, m: int = 3, ref_num: int = 1000, k: int | None = None)

Bases: WFG

Base class for the Walking Fish Group benchmark problems.

Decision variables follow the PlatEMO scale: lower = 0 and upper = [2, 4, ..., 2*d]. The position parameter k defaults to m - 1 and should be a multiple of m - 1.

evaluate(X: torch.Tensor) → torch.Tensor

class evomo.problems.numerical.wfg.WFG7(d: int | None = None, m: int = 3, ref_num: int = 1000, k: int | None = None)

Bases: WFG

Base class for the Walking Fish Group benchmark problems.

Decision variables follow the PlatEMO scale: lower = 0 and upper = [2, 4, ..., 2*d]. The position parameter k defaults to m - 1 and should be a multiple of m - 1.

evaluate(X: torch.Tensor) → torch.Tensor

class evomo.problems.numerical.wfg.WFG8(d: int | None = None, m: int = 3, ref_num: int = 1000, k: int | None = None)

Bases: WFG

Base class for the Walking Fish Group benchmark problems.

Decision variables follow the PlatEMO scale: lower = 0 and upper = [2, 4, ..., 2*d]. The position parameter k defaults to m - 1 and should be a multiple of m - 1.

evaluate(X: torch.Tensor) → torch.Tensor

class evomo.problems.numerical.wfg.WFG9(d: int | None = None, m: int = 3, ref_num: int = 1000, k: int | None = None)

Bases: WFG

Base class for the Walking Fish Group benchmark problems.

Decision variables follow the PlatEMO scale: lower = 0 and upper = [2, 4, ..., 2*d]. The position parameter k defaults to m - 1 and should be a multiple of m - 1.

evaluate(X: torch.Tensor) → torch.Tensor