SoPlex is an optimization package for solving linear programming problems (LPs) based on an advanced implementation of the primal and dual revised simplex algorithm. It provides special support for ...

Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...

The original version of this story appeared in Quanta Magazine. In 1939, upon arriving late to his statistics course at UC Berkeley, George Dantzig—a first-year graduate student—copied two problems ...

The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get any better. In 1939, upon arriving late to his statistics course at the ...

In the evolving landscape of decision intelligence, few mathematical breakthroughs have had as profound an impact as linear programming. At the heart of this revolutionary approach stands a brilliant ...

1 Department of Basic Sciences and Humanities, University of Asia Pacific, Dhaka, Bangladesh. 2 General Education Department, City University, Dhaka, Bangladesh. 3 Department of Mathematics, ...

Since its creation more than two decades ago by Daniel Spielman (above) and Shang-hua Teng, smoothed analysis has been used to analyze performance of algorithms other than the simplex method, ...

Image segmentation technology has been widely applied in industry, agriculture, military fields, etc. Among all the image segmentation methods, thresholding is one of the most widely used, because it ...

This is a Common Lisp library for solving linear programming problems. It's designed to provide a high-level and ergonomic API for specifying linear programming problems as lisp expressions. The core ...

As a powerful modelling method, piecewise linear neural networks (PWLNNs) have proven successful in various fields, most recently in deep learning. To apply PWLNN methods, both the representation and ...