smt_optim.benchmarks.multiobj package

Submodules

smt_optim.benchmarks.multiobj.constrained module

class BNH

Bases: BenchmarkProblem

bounds: ndarray = None

constraints: list = None

f1(x)

f2(x)

g1(x)

g2(x)

name: str = None

num_cstr: int = None

num_dim: int = None

num_fidelity: int = None

num_obj: int = None

objective: Callable | list[Callable] = None

set_dim(dim)

tags: list = None

class OSY

Bases: BenchmarkProblem

bounds: ndarray = None

constraints: list = None

f1(x)

f2(x)

g1(x)

g2(x)

g3(x)

g4(x)

g5(x)

g6(x)

name: str = None

num_cstr: int = None

num_dim: int = None

num_fidelity: int = None

num_obj: int = None

objective: Callable | list[Callable] = None

set_dim(dim)

tags: list = None

class TNK

Bases: BenchmarkProblem

bounds: ndarray = None

constraints: list = None

f1(x)

f2(x)

g1(x)

g2(x)

name: str = None

num_cstr: int = None

num_dim: int = None

num_fidelity: int = None

num_obj: int = None

objective: Callable | list[Callable] = None

set_dim(dim)

tags: list = None

smt_optim.benchmarks.multiobj.zdt module

Reference: Towards a multi-fidelity & multi-objective Bayesian optimization efficient algorithm Rémy Charayron, Thierry Lefebvre, Nathalie Bartoli, Joseph Morlier

With multi-fidelity variant? ZDT1, ZDT2, ZDT3, ZDT5 (w/ cstr)

DTLZ5

class ZDT1

Bases: BenchmarkProblem

bounds: ndarray = None

constraints: list = None

f1(x)

f2(x)

g(x)

h(f1, g)

name: str = None

num_cstr: int = None

num_dim: int | str = None

num_fidelity: int = None

num_obj: int = None

objective: Callable | list[Callable] = None

set_dim(dim)

tags: list = None

class ZDT2

Bases: BenchmarkProblem

bounds: ndarray = None

constraints: list = None

f1(x)

f2(x)

g(x)

h(f1, g)

name: str = None

num_cstr: int = None

num_dim: int | str = None

num_fidelity: int = None

num_obj: int = None

objective: Callable | list[Callable] = None

set_dim(dim)

tags: list = None

class ZDT3

Bases: BenchmarkProblem

bounds: ndarray = None

constraints: list = None

f1(x)

f2(x)

g(x)

h(f1, g)

name: str = None

num_cstr: int = None

num_dim: int | str = None

num_fidelity: int = None

num_obj: int = None

objective: Callable | list[Callable] = None

set_dim(dim)

tags: list = None

class ZDT4

Bases: BenchmarkProblem

bounds: ndarray = None

constraints: list = None

f1(x)

f2(x)

g(x)

h(f1, g)

name: str = None

num_cstr: int = None

num_dim: int | str = None

num_fidelity: int = None

num_obj: int = None

objective: Callable | list[Callable] = None

set_dim(dim)

tags: list = None

smt_optim.benchmarks.multiobj.zdt_mf module

Reference: Towards a multi-fidelity & multi-objective Bayesian optimization efficient algorithm Rémy Charayron, Thierry Lefebvre, Nathalie Bartoli, Joseph Morlier

With multi-fidelity variant? ZDT1, ZDT2, ZDT3, ZDT5 (w/ cstr)

DTLZ5

class DTLZ5

Bases: BenchmarkProblem

bounds: ndarray = None

constraints: list = None

f1(x)

f1_lf(x)

f2(x)

f2_lf(x)

g(x)

g_lf(x)

name: str = None

num_cstr: int = None

num_dim: int | str = None

num_fidelity: int = None

num_obj: int = None

objective: Callable | list[Callable] = None

set_dim(dim)

tags: list = None

u(x: ndarray)

Module contents