# {py:mod}`evox.algorithms.mo.rveaa`

```{py:module} evox.algorithms.mo.rveaa
```

```{autodoc2-docstring} evox.algorithms.mo.rveaa
:allowtitles:
```

## Module Contents

### Classes

````{list-table}
:class: autosummary longtable
:align: left

* - {py:obj}`RVEAa <evox.algorithms.mo.rveaa.RVEAa>`
  - ```{autodoc2-docstring} evox.algorithms.mo.rveaa.RVEAa
    :summary:
    ```
````

### API

`````{py:class} RVEAa(pop_size: int, n_objs: int, lb: torch.Tensor, ub: torch.Tensor, alpha: float = 2.0, fr: float = 0.1, max_gen: int = 100, selection_op: typing.Optional[typing.Callable] = None, mutation_op: typing.Optional[typing.Callable] = None, crossover_op: typing.Optional[typing.Callable] = None, device: torch.device | None = None)
:canonical: evox.algorithms.mo.rveaa.RVEAa

Bases: {py:obj}`evox.core.Algorithm`

```{autodoc2-docstring} evox.algorithms.mo.rveaa.RVEAa
```

```{rubric} Initialization
```

```{autodoc2-docstring} evox.algorithms.mo.rveaa.RVEAa.__init__
```

````{py:method} init_step()
:canonical: evox.algorithms.mo.rveaa.RVEAa.init_step

```{autodoc2-docstring} evox.algorithms.mo.rveaa.RVEAa.init_step
```

````

````{py:method} _rv_adaptation(pop_obj: torch.Tensor)
:canonical: evox.algorithms.mo.rveaa.RVEAa._rv_adaptation

```{autodoc2-docstring} evox.algorithms.mo.rveaa.RVEAa._rv_adaptation
```

````

````{py:method} _no_rv_adaptation(pop_obj: torch.Tensor)
:canonical: evox.algorithms.mo.rveaa.RVEAa._no_rv_adaptation

```{autodoc2-docstring} evox.algorithms.mo.rveaa.RVEAa._no_rv_adaptation
```

````

````{py:method} _mating_pool()
:canonical: evox.algorithms.mo.rveaa.RVEAa._mating_pool

```{autodoc2-docstring} evox.algorithms.mo.rveaa.RVEAa._mating_pool
```

````

````{py:method} _rv_regeneration(pop_obj: torch.Tensor, v: torch.Tensor)
:canonical: evox.algorithms.mo.rveaa.RVEAa._rv_regeneration

```{autodoc2-docstring} evox.algorithms.mo.rveaa.RVEAa._rv_regeneration
```

````

````{py:method} _batch_truncation(pop: torch.Tensor, obj: torch.Tensor)
:canonical: evox.algorithms.mo.rveaa.RVEAa._batch_truncation

```{autodoc2-docstring} evox.algorithms.mo.rveaa.RVEAa._batch_truncation
```

````

````{py:method} _no_batch_truncation(pop: torch.Tensor, obj: torch.Tensor)
:canonical: evox.algorithms.mo.rveaa.RVEAa._no_batch_truncation

```{autodoc2-docstring} evox.algorithms.mo.rveaa.RVEAa._no_batch_truncation
```

````

````{py:method} _update_pop_and_rv(survivor: torch.Tensor, survivor_fit: torch.Tensor)
:canonical: evox.algorithms.mo.rveaa.RVEAa._update_pop_and_rv

```{autodoc2-docstring} evox.algorithms.mo.rveaa.RVEAa._update_pop_and_rv
```

````

````{py:method} step()
:canonical: evox.algorithms.mo.rveaa.RVEAa.step

```{autodoc2-docstring} evox.algorithms.mo.rveaa.RVEAa.step
```

````

`````