evomo.problems.constrained.mw#

Classes#

`MW`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW1`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW2`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW3`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW4`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW5`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW6`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW7`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW8`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW9`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW10`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW11`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW12`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW13`	Base class for Constrained Multi-objective Optimization Problems (CMOP).
`MW14`	Base class for Constrained Multi-objective Optimization Problems (CMOP).

Module Contents#

class evomo.problems.constrained.mw.MW(prob_id: int = None, d: int = None, m: int = None, ref_num: int = 1000, **kwargs)#

Bases: evomo.problems.constrained.base.CMOP

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

device#

ref_num = 1000#

m = None#

static LA1(A, B, C, D, theta)#

static LA2(A, B, C, D, theta)#

static LA3(A, B, C, D, theta)#

g1(X)#

g2(X)#

g3(X)#

class evomo.problems.constrained.mw.MW1(m=2, d=10, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW2(m=2, d=10, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW3(m=2, d=10, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW4(d=10, m=3, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW5(m=2, d=10, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW6(m=2, d=10, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW7(m=2, d=10, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW8(d=10, m=3, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW9(m=2, d=10, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW10(m=2, d=10, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW11(m=2, d=10, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW12(m=2, d=10, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW13(m=2, d=10, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#

class evomo.problems.constrained.mw.MW14(d=10, m=3, ref_num: int = 1000, **kwargs)#

Bases: MW

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

fn(X: torch.Tensor) → torch.Tensor#

pf()#