Download
High level optimization routines in Fortran 95 for optimization problems using a genetic algorithm
with elitism, steady-state-reproduction, dynamic operator scoring by merit, no-duplicates-in-population. Chromosome representation may be integer-array, real-array, permutation-array, character-array.
Single objective and multi-objective maximization routines are present. Possible to incorporate own crossover and mutation operators exclusively or in addition to standard operators that are included by default.
The aim is to make it possible to quickly develop a high performance GA for any given application problem.
Features
- elitism
- no duplicates in population
- dynamic operator selection probabilities based on recent performance
- steady state reproduction
Follow GA-tools
Other Useful Business Software
Gen AI apps are built with MongoDB Atlas
MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of GA-tools!