Homepage: github.com/structurely/csa.
Coupled simulated annealing (CSA) is a generalization of simulated annealing (SA), which is an optimization algorithm that doesn’t use any information about the derivates of a function. The original paper describing CSA can be found here:
ftp://ftp.esat.kuleuven.be/sista/sdesouza/papers/CSA2009accepted.pdf
Essentially, CSA is like multiple simulated annealing (i.e. m independent SA processes run in parallel), except that the acceptance probability at each step is calculated as a function of the current state across all m processes. For a more complete description of the general CSA algorithm, see Description of CSA.
Installation
Using pip:
pip install pycsa
Directly from GitHub:
pip install git+https://github.com/structurely/csa.git
Usage
See examples/travelling_salesman.ipynb for an example of CSA applied to the travelling salesman problem (TSP).
Contributing
Feel free to submit issues at github.com/structurely/csa/issues and pull requests to the dev branch: github.com/structurely/csa/tree/dev.
License
See LICENSE.txt.
1 maintainer
Metadata
1 maintainer
Release files for pycsa 0.1.3
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| pycsa-0.1.3-py2-none-any.whl | Python 2 | none | any | Details |
Total release size: 11.6 kB
Release files / pycsa-0.1.3.tar.gz
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| Size | 6.9 kB |
| Tags | Python 2 |
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