Skip to main content

Python implementation of coupled simulated annealing (CSA)

Project description

Build Status PyPI


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:

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.


Using pip:

pip install pycsa

Directly from GitHub:

pip install git+


See examples/travelling_salesman.ipynb for an example of CSA applied to the travelling salesman problem (TSP).


Feel free to submit issues at and pull requests to the dev branch:


See LICENSE.txt.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pycsa-0.1.3.tar.gz (4.8 kB view hashes)

Uploaded source

Built Distribution

pycsa-0.1.3-py2-none-any.whl (6.9 kB view hashes)

Uploaded py2

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page