`evox.problems.numerical.dtlz`#

Module Contents#

`DTLZ`	Base class for DTLZ test suite problems in multi-objective optimization.
`DTLZ1`
`DTLZ2`
`DTLZ3`
`DTLZ4`
`DTLZ5`
`DTLZ6`
`DTLZ7`

class evox.problems.numerical.dtlz.DTLZ(d: int = None, m: int = None, ref_num: int = 1000)[source]#

Bases: evox.core.Problem

Base class for DTLZ test suite problems in multi-objective optimization.

Inherit this class to implement specific DTLZ problem variants.

Parameters:

Initialization

Override the setup method to initialize the parameters

abstractmethod evaluate(X: torch.Tensor) → torch.Tensor[source]#

Abstract method to evaluate the objective values for given decision variables.

Parameters:: X – A tensor of shape (n, d), where n is the number of solutions and d is the number of decision variables.
Returns:: A tensor of shape (n, m) representing the objective values for each solution.

Return the Pareto front for the problem.

class evox.problems.numerical.dtlz.DTLZ1(d: int = 7, m: int = 3, ref_num: int = 1000)[source]#

class evox.problems.numerical.dtlz.DTLZ2(d: int = 12, m: int = 3, ref_num: int = 1000)[source]#

class evox.problems.numerical.dtlz.DTLZ3(d: int = 12, m: int = 3, ref_num: int = 1000)[source]#

class evox.problems.numerical.dtlz.DTLZ4(d: int = 12, m: int = 3, ref_num: int = 1000)[source]#

class evox.problems.numerical.dtlz.DTLZ5(d: int = 12, m: int = 3, ref_num: int = 1000)[source]#

class evox.problems.numerical.dtlz.DTLZ6(d: int = 12, m: int = 3, ref_num: int = 1000)[source]#

class evox.problems.numerical.dtlz.DTLZ7(d: int = 21, m: int = 3, ref_num: int = 1000)[source]#