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Python package for executing optimization algorithm.

License: MIT License

Python 100.00%
adaptive-algorithm adaptive-evolution decision-variables evolutionary-algorithm evolutionary-algorithms genetic-algorithm genetic-algorithms genetic-optimization-algorithm optimization optimization-algorithm optimization-algorithm-library optimization-problem optimization-process optimization-tools

optimization's Issues

Stop conditions introduction

Design, implement, test and document stop conditions.

Possible stop conditions:

  • time restriction (mandatory)
  • satisfying solution
  • iterations without progress
  • time without progress

TODO:

  • adjust to self adaptive algorithms
  • compatible with all algorithms types

Fix 'log_function_code' output

Rework function optimization.logging.utilities.log_function_code to return code in proper format (indentation, new lines etc.)

Logger instroduction

Design, implement, test and document logger functionality.

TODO:

  • setting logging verbosity and logs format
  • include following data in logs:
    • best solution
    • optimization problem
    • configuration of optimization algorithm with stop conditions
    • all solutions found
  • adjust to self adaptive algorithm (two level optimization)

Coverage and other fancy icons

Update readme.md to have properly displayed links to:

  • PyPI
  • coverage report
  • static analysis status
  • other fancy gadgets?

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