Welcome to Moead-Framework’s documentation!

The Multi-objective evolutionary algorithm based on decomposition (MOEA/D) is a general-purpose algorithm for approximating the Pareto set of multi-objective optimization problems. It decomposes the original multi-objective problem into a number of single-objective optimization sub-problems and then uses an evolutionary process to optimize these sub-problems simultaneously and cooperatively. MOEA/D is a state-of-art algorithm in aggregation-based approaches for multi-objective optimization.

The goal of the moead-framework python package is to provide a modular framework for scientists and researchers interested in experimenting with MOEA/D and its numerous variants.

If you have any questions about the framework or the project, feel free to create a new discussion on github: https://github.com/moead-framework/framework/discussions.

• Installation
  • Installing via pip
  • Download the sources
  • Dependencies
  • Run tests
• User guide
  • Overview
  • Problem & Solution
  • Algorithm
  • Sub-problem selection strategy
  • Aggregation functions
  • Mating Selector
  • Offspring generator
  • Termination criteria
• Tutorials
  • Implement your own problem
  • Implement your own algorithm
  • Manage the reproducibility of results
  • Save data with the framework
  • Extract and plot the Pareto front
• Library Reference
  • Main components
  • Other components
  • Problems
  • Tools
• Examples
  • Optimise mnk-landscapes with MOEA/D
  • Create your own variant of MOEA/D with the modularity of the framework
  • Update the behavior of MOEA/D without using inner components
• References
• Contributing
  • Pull Request Process
  • You want to share a bug ?
  • Support
  • Code of Conduct