Optimization Algorithm Toolkit is a workbench and toolkit for developing, evaluating, and playing with classical and state-of-the-art optimization algorithms on standard benchmark problem domains. It includes reference algorithm implementations, graphing, visualizations, and much more.
|Tags||Scientific/Engineering Artificial Intelligence Bioinformatics Mathematics Visualization|
Release Notes: A major restructuring of the API was done. Bugs were fixed everywhere. A new (and beta) experimenter API and graphical user interface were added. Notably, the new experimenter includes the standard statistical hypothesis tests for normality and comparison of algorithm results.
Release Notes: This release includes many framework and graphical interface fixes, as well as a few new algorithms to play with.
Release Notes: This release added a graph coloring problem, binary character recognition, and binary trap function problem domains. Many algorithm implementations were added as well as a ton of bugfixes in the core framework.
Release Notes: This release is focused on the core framework and testing rather than on adding algorithms and problems. As such, the software is a lot more mature in this release. Bugs have been fixed and many feature requests added. This release includes junit tests and code examples for using the API.
Release Notes: This release has 4 different benchmark problem domains, including: Function Optimization (56 instances and 18 algorithms); Huygens Probe Benchmark Suite (fractal function optimization); Travelling Salesman Problem TSP (15 instances and 10 algorithms); and Protein Folding HP Model (14 instances and 1 algorithm).