Welcome to pyHMS’s documentation!
pyHMS is a Python implementation of Hierarchic Memetic Strategy (HMS).
The Hierarchic Memetic Strategy is a stochastic global optimizer designed to tackle highly multimodal problems. It is a composite global optimization strategy consisting of a multi-population evolutionary strategy and some auxiliary methods. The HMS makes use of a dynamically-evolving data structure that provides an organization among the component populations. It is a tree with a fixed maximal height and variable internal node degree. Each component population is governed by a particular optimization engine. This package provides a simple python implementation.
Check out the Usage section for further information, including how to install the project.
Note
This project is under active development.
Contents
- Home
- Hierarchic Memetic Strategy (HMS)
- Usage
- Inspecting results
- Sprouting Mechanisms
- Adding Custom Demes to pyHMS
- Stop Conditions
- Problem
- Configuration Options