Neighbourhoods
==============

In simulated annealing, a neighbourhood function defines the set of candidate solutions that can be reached from the
current state in a single step. The quality and structure of the neighbourhood are crucial for the algorithm's
performance, as they determine how the search space is explored.
The :class:`~altbacken.core.neighbourhood.Neighbourhood` protocol defines the interface for these functions. A
neighbourhood is a callable that takes an :class:`~altbacken.core.state.AnnealingState` and returns a new candidate
solution of the same type.

.. include:: numeric.rst
.. include:: permutation.rst

Custom Neighbourhoods
---------------------

You can implement your own neighbourhood by creating a class or function that follows the
:class:`~altbacken.core.neighbourhood.Neighbourhood` protocol.

.. code-block:: python

   from altbacken.core.state import AnnealingState

   def my_custom_neighbourhood(state: AnnealingState[float]) -> float:
       # Generate a new solution based on the current one
       return state.current_solution + 0.1