Moptipy

Latest version: v0.9.136

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0.9.37

The [general MA](https://thomasweise.github.io/moptipy/moptipy.algorithms.so.html#module-moptipy.algorithms.so.general_ma) is a generalized version of the (&x3BC;+&x3BB;) MA that can additionally be configured with a [fitness assignment process](https://thomasweise.github.io/moptipy/moptipy.algorithms.so.fitnesses.html) and both survival and mating [selection algorithms](https://thomasweise.github.io/moptipy/moptipy.algorithms.modules.html#module-moptipy.algorithms.modules.selection).

We also implemented several code quality improvements based on the suggestions by [version 0.0.212](https://pypi.org/project/ruff/0.0.212/) of [`ruff`](https://pypi.org/project/ruff/), a really awesome static analysis tool checking a wide range of coding conventions.

0.9.36

The [`from_starting_point`](https://thomasweise.github.io/moptipy/moptipy.api.html#moptipy.api.subprocesses.from_starting_point) subprocess routine now creates a process which also updates the current-best solution if a new, equally good solution is discovered (instead of only updating it on improvements). This allows for drift, i.e., for a behavior more similar to [RLS](https://thomasweise.github.io/moptipy/moptipy.algorithms.so.html#module-moptipy.algorithms.so.rls) as opposed to strictly-improving [hill climbers](https://thomasweise.github.io/moptipy/moptipy.algorithms.so.html#module-moptipy.algorithms.so.hill_climber) in [Memetic Algorithms](https://thomasweise.github.io/moptipy/moptipy.algorithms.so.html#module-moptipy.algorithms.so.ma) (MAs).

We also added a [hard-coded Memetic Algorithm](https://thomasweise.github.io/moptipy/moptipy.algorithms.so.html#module-moptipy.algorithms.so.ma) using RLS as internal local search. This algorithm is more efficient as it has less overhead compared to an identically configured general [MA](https://thomasweise.github.io/moptipy/moptipy.algorithms.so.html#module-moptipy.algorithms.so.ma), but will take exactly the same path through the search space.

Finally, we improved the documentation of the [Job Shop Scheduling](https://thomasweise.github.io/moptipy/moptipy.examples.jssp.html#module-moptipy.examples.jssp) example problem domain.

0.9.35

improved documentation and small bugfix for ma

0.9.34

Several Bug Fixes and Improvements

0.9.33

Added Example and Fixed Error in Unit Test

0.9.32

Now Also Applying Local Search to Initial Random Solutions in Memetic Algorithm (MA)

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