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NSGA2 algorithm performance investigation for different multi-objective optimization problems.

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Installing requirements

sudo pip install deap

Licence

LGPL, same as in DEAP project (see Distributed Evolutionary Algorithms in Python).

Changes

  • tools.py Added new benchmark tool: uniformity.
  • problems.py Added two new bi-objective problems: EP1, EP2.
  • problems.py Added function decorator, which calculates how many unique calles were made.
  • nsga2.py slightly modified interface to work with function wrapper.

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NSGA2 algorithm performance investigation for different multi-objective optimization problems.

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