oj! Algorithms

With the release of ojAlgo v57.0.0 comes significant changes to both the LP and QP solvers, including improvements to the revised simplex and an entirely new ADMM QP solver alongside the existing active-set solver.

ojAlgo v57.0.0 has been released!

Two recent releases with a lot of QP related news.

ojAlgo aims to have the best set of pure Java solvers available, and to be roughly on par with good native code solvers when the models are not too big or numerically challenging.

The Traveling Salesman Problem (TSP) is a classic optimization problem in which a salesman must visit a set of cities exactly once and return to the starting city, while minimizing the total travel distance.

Playing around with various AI tools, as is common nowadays, I asked the tool to search the internet and summarise common questions, complaints and misconceptions about ojAlgo.

This post aims to demonstrate how to make a solver usable from ExpressionsBasedModel.

This post describes how to do clustering with ojAlgo.

The One Billion Row Challenge (1BRC) is a fun exploration of how far modern Java can be pushed for aggregating one billion rows from a text file.

The Fast Fourier Transform (FFT) algorithm to calculate discrete Fourier transforms (DFT) is a recent addition to ojAlgo.