Platypus - Multiobjective Optimization in Python

Platypus is a framework for evolutionary computing in Python with a focus on multiobjective evolutionary algorithms (MOEAs). It differs from existing optimization libraries, including PyGMO, Inspyred, DEAP, and Scipy, by providing optimization algorithms and analysis tools for multiobjective optimization.

• Getting Started
  • Installing Platypus
  • A Simple Example
  • Defining Unconstrained Problems
  • Defining Constrained Problems
• Decsion Variable Types
  • Real
  • Binary
  • Integer
  • Permutation
  • Subset
• Experimenter
  • Basic Use
  • Parallelization
  • Comparing Algorithms Visually
• Platypus API
  • platypus.algorithms module
  • platypus.config module
  • platypus.core module
  • platypus.distance module
  • platypus.errors module
  • platypus.evaluator module
  • platypus.experimenter module
  • platypus.filters module
  • platypus.indicators module
  • platypus.io module
  • platypus.mpipool module
  • platypus.operators module
  • platypus.problems module
  • platypus.types module
  • platypus.weights module