evomo.problems.numerical.lsmop#

Classes#

LSMOP

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

LSMOP1

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

LSMOP2

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

LSMOP3

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

LSMOP4

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

LSMOP5

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

LSMOP6

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

LSMOP7

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

LSMOP8

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

LSMOP9

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

Functions#

schwefel_func(→ torch.Tensor)

Module Contents#

evomo.problems.numerical.lsmop.schwefel_func(x: torch.Tensor) → torch.Tensor#
class evomo.problems.numerical.lsmop.LSMOP(d=None, m=None, ref_num=1000)#

Bases: evox.core.Problem

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

References:
[1] R. Cheng, Y. Jin, M. Olhofer, and B. Sendhoff, “Test Problems for Large-Scale

Multiobjective and Many-Objective Optimization,” IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4108-4121, 2017. Available: https://ieeexplore.ieee.org/abstract/document/7553457

Parameters:

  • d – number of decision variables

  • m – number of objectives

  • ref_num – number of reference points, defaults to 1000

nk = 5#
m = 3#
d = 300#
ref_num = 1000#
sublen#
len#
sphere#
griewank#
rosenbrock#
ackley#
rastrigin#
schwefel#
evaluate(X: torch.Tensor)#
pf()#
class evomo.problems.numerical.lsmop.LSMOP1(d=None, m=None, ref_num=1000)#

Bases: LSMOP

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

References:
[1] R. Cheng, Y. Jin, M. Olhofer, and B. Sendhoff, “Test Problems for Large-Scale

Multiobjective and Many-Objective Optimization,” IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4108-4121, 2017. Available: https://ieeexplore.ieee.org/abstract/document/7553457

Parameters:

  • d – number of decision variables

  • m – number of objectives

  • ref_num – number of reference points, defaults to 1000

class evomo.problems.numerical.lsmop.LSMOP2(d=None, m=3, ref_num=1000)#

Bases: LSMOP

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

References:
[1] R. Cheng, Y. Jin, M. Olhofer, and B. Sendhoff, “Test Problems for Large-Scale

Multiobjective and Many-Objective Optimization,” IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4108-4121, 2017. Available: https://ieeexplore.ieee.org/abstract/document/7553457

Parameters:

  • d – number of decision variables

  • m – number of objectives

  • ref_num – number of reference points, defaults to 1000

class evomo.problems.numerical.lsmop.LSMOP3(d=None, m=None, ref_num=1000)#

Bases: LSMOP

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

References:
[1] R. Cheng, Y. Jin, M. Olhofer, and B. Sendhoff, “Test Problems for Large-Scale

Multiobjective and Many-Objective Optimization,” IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4108-4121, 2017. Available: https://ieeexplore.ieee.org/abstract/document/7553457

Parameters:

  • d – number of decision variables

  • m – number of objectives

  • ref_num – number of reference points, defaults to 1000

class evomo.problems.numerical.lsmop.LSMOP4(d=None, m=None, ref_num=1000)#

Bases: LSMOP

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

References:
[1] R. Cheng, Y. Jin, M. Olhofer, and B. Sendhoff, “Test Problems for Large-Scale

Multiobjective and Many-Objective Optimization,” IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4108-4121, 2017. Available: https://ieeexplore.ieee.org/abstract/document/7553457

Parameters:

  • d – number of decision variables

  • m – number of objectives

  • ref_num – number of reference points, defaults to 1000

class evomo.problems.numerical.lsmop.LSMOP5(d=None, m=None, ref_num=1000)#

Bases: LSMOP

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

References:
[1] R. Cheng, Y. Jin, M. Olhofer, and B. Sendhoff, “Test Problems for Large-Scale

Multiobjective and Many-Objective Optimization,” IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4108-4121, 2017. Available: https://ieeexplore.ieee.org/abstract/document/7553457

Parameters:

  • d – number of decision variables

  • m – number of objectives

  • ref_num – number of reference points, defaults to 1000

class evomo.problems.numerical.lsmop.LSMOP6(d=None, m=None, ref_num=1000)#

Bases: LSMOP5

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

References:
[1] R. Cheng, Y. Jin, M. Olhofer, and B. Sendhoff, “Test Problems for Large-Scale

Multiobjective and Many-Objective Optimization,” IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4108-4121, 2017. Available: https://ieeexplore.ieee.org/abstract/document/7553457

Parameters:

  • d – number of decision variables

  • m – number of objectives

  • ref_num – number of reference points, defaults to 1000

class evomo.problems.numerical.lsmop.LSMOP7(d=None, m=None, ref_num=1000)#

Bases: LSMOP5

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

References:
[1] R. Cheng, Y. Jin, M. Olhofer, and B. Sendhoff, “Test Problems for Large-Scale

Multiobjective and Many-Objective Optimization,” IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4108-4121, 2017. Available: https://ieeexplore.ieee.org/abstract/document/7553457

Parameters:

  • d – number of decision variables

  • m – number of objectives

  • ref_num – number of reference points, defaults to 1000

class evomo.problems.numerical.lsmop.LSMOP8(d=None, m=None, ref_num=1000)#

Bases: LSMOP5

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

References:
[1] R. Cheng, Y. Jin, M. Olhofer, and B. Sendhoff, “Test Problems for Large-Scale

Multiobjective and Many-Objective Optimization,” IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4108-4121, 2017. Available: https://ieeexplore.ieee.org/abstract/document/7553457

Parameters:

  • d – number of decision variables

  • m – number of objectives

  • ref_num – number of reference points, defaults to 1000

class evomo.problems.numerical.lsmop.LSMOP9(d=None, m=None, ref_num=1000)#

Bases: LSMOP

The LSMOP test suite for large-scale multiobjective and many-objective optimization.

References:
[1] R. Cheng, Y. Jin, M. Olhofer, and B. Sendhoff, “Test Problems for Large-Scale

Multiobjective and Many-Objective Optimization,” IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4108-4121, 2017. Available: https://ieeexplore.ieee.org/abstract/document/7553457

Parameters:

  • d – number of decision variables

  • m – number of objectives

  • ref_num – number of reference points, defaults to 1000