Description Usage Arguments Value Note Examples

View source: R/exploreEfficientSet.R

Explores a locally efficient set separately along the gradients of the two objectives
`fn1`

and `fn2`

. Both explorations initially start in point `ind`

. Such
explorations obviously are only reasonable, if `ind`

is a locally efficient point.
See `findLocallyEfficientPoint`

for further details.

1 2 3 4 |

`ind` |
[ |

`fn1` |
[ |

`fn2` |
[ |

`gradient.list` |
[ |

`max.no.steps.exploration` |
[ |

`exploration.step` |
[ |

`prec.grad` |
[ |

`prec.norm` |
[ |

`prec.angle` |
[ |

`lower` |
[ |

`upper` |
[ |

`check.data` |
[ |

`show.info` |
[ |

[`list(4)`

]

Returns a list with four elements. The first one provides the points that were found
to be part of the efficient set.

The second element lists the corresponding number of performed function evaluations.

The third and fourth elements are lists, containing information on the edges of the
efficient set. This information consists of a `logical`

indicating whether
it could be confirmed that the found efficient set definitely is only a local efficient
set. Important note: a value of `FALSE`

does not imply that the found efficient set
has to be globally efficient, as it could also be a multi-objective trap. In addition
those two sublists also contain the actual positions of the evaluated points outside
the efficient set, their single-objective gradients as well as the number of function
evaluations (per objective) performed to compute these gradients.

Note that these (up to two) points (`end1$external`

and `end2$external`

)
are reasonable starting points for a gradient descent towards a better efficient set.

ATTENTION: Only turn off the sanity checks (`check.data = FALSE`

),
if you can ensure that all input parameters are provided in the correct format.

1 2 3 4 5 6 | ```
# Define two single-objective test problems:
fn1 = function(x) sum((x - c(0.2, 1))^2)
fn2 = function(x) 2 * x[1]^2 - x[1] * x[2] + 0.3 * x[2]^2
# c(0.2, 1) is obviously a local optimum of fn1, so let's explore the efficient set from there:
exploreEfficientSet(c(0.2, 1), fn1, fn2, max.no.steps.exploration = 50L, exploration.step = 0.05)
``` |

kerschke/mogsa documentation built on Oct. 27, 2018, 12:13 a.m.

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