This repository contains a continuous GA implementation and a generational (traditional) GA implementation, both written in python.
The purpose of this repository is to see of continuous GA is good enough (or better?) to be used as a drop-in replacement for generational GA. The outcome of these tests will be used for decision making in the FPGA design process.
Generational (traditional) GA is the classic GA algorithm which focuses on manipulating generations in concrete steps.
Continuous GA does not have a concept of generations, but rather continously performs GA operations on a single population.
VLSI Hardware Design for Genetic Algorithms and Its Parallel and Distributed Extensions