Requirements

• Requires at least Python 2.6 (not compatible with Python 3+).
• Numpy and Matplotlib are required if the line plot observer is used.
• Parallel Python (pp) is required if parallel_evaluation_pp is used.

License

This package is distributed under the GNU General Public License version 3.0 (GPLv3). This license can be found online at http://www.opensource.org/licenses/gpl-3.0.html.

Package Structure

ECsPy consists of the following modules:

• analysis.py -- provides tools for analyzing the results of an EC
• archivers.py -- defines useful archiving methods, particularly for EMO algorithms
• benchmarks.py -- defines several single- and multi-objective benchmark optimization problems
• ec.py -- provides the basic framework for an EvolutionaryComputation and specific ECs
• emo.py -- provides the Pareto class for multiobjective optimization along with specific EMOs (e.g. NSGA-II)
• evaluators.py -- defines useful evaluation schemes, such as parallel evaluation
• migrators.py -- defines a few built-in migrators, including migration via network and migration among concurrent processes
• observers.py -- defines a few built-in observers, including screen, file, and plotting observers
• replacers.py -- defines standard replacement schemes such as generational and steady-state replacement
• selectors.py -- defines standard selectors (e.g., tournament)
• swarm.py -- provides a basic particle swarm optimizer
• terminators.py -- defines standard terminators (e.g., exceeding a maximum number of generations)
• topologies.py -- defines standard topologies for particle swarms
• variators.py -- defines standard variators (crossover and mutation schemes such as n-point crossover)

Resources

• Homepage: http://ecspy.googlecode.com
• Email: aaron.lee.garrett@gmail.com