esa/pygmo2

A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.

What it solves

It provides a unified interface for massively parallel optimization, allowing users to deploy complex optimization algorithms and problems across parallel environments more easily.

How it works

It acts as a scientific Python library that standardizes how optimization algorithms and problems are defined and interacted with, facilitating their execution in parallel architectures.

Who it’s for

Researchers, teachers, and scientists who need to perform large-scale global multiobjective optimization.

Highlights

  • Massively parallel optimization capabilities
  • Unified interface for algorithms and problems
  • Support for global multiobjective optimization
  • Easy deployment in parallel environments

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