Python microframework for building nature-inspired algorithms
NiaPy
Nature-inspired algorithms are a very popular tool for solving optimization problems. Numerous variants of nature-inspired algorithms have been developed (paper 1, paper 2) since the beginning of their era. To prove their versatility, those were tested in various domains on various applications, especially when they are hybridized, modified or adapted. However, implementation of nature-inspired algorithms is sometimes a difficult, complex and tedious task. In order to break this wall, NiaPy is intended for simple and quick use, without spending time for implementing algorithms from scratch.
Our mission is to build a collection of nature-inspired algorithms and create a simple interface for managing the optimization process. NiaPy offers:
- numerous optimization problem implementations,
- use of various nature-inspired algorithms without struggle and effort with a simple interface,
- easy comparison between nature-inspired