Simulated Annealing (SA) has been initially proposed in Optimization by Simulated Annealing as an optimization heuristic. Multi-objective Simulated Annealing (MOSA) extends the original, single-objective SA to approximate the Pareto front in multi-objective optimization problems. A comprehensive discussion on MOSA and its algorithm variants can be found in Multi-objective Simulated Annealing: Principles and Algorithm Variants.
This library implements the MOSA algorithm in Python. Jupyter notebooks in the examples directory provide usage examples.
The easiest way to install MOSA is using pip:
pip install mosa
The code is provided "as is," with no guarantees regarding the accuracy of its results. The author assumes no responsibility for any losses arising from the use of the code. If you have any questions, comments, or suggestions about the code, feel free to send a message or open an issue on the project's GitHub repository.