Constraints are the limitations or restrictions that affect the feasible region of a linear programming problem. They represent the conditions or requirements that must be satisfied by the ...

Learn how to tackle critical dependencies in your program when faced with resource constraints. This guide provides practical strategies for program managers.

This repo is a record of my attempt to research and learn Prolog programming using Constraint Logic Programming (CLP). The work here was greatly inspired along by the Power of Prolog series, reading ...

We describe a new active-set, cutting-plane Constraint Optimal Selection Technique (COST) for solving general linear programming problems. We describe strategies to bound the initial problem and ...

Datasets related to the paper: "Improving the efficiency of Euclidean TSP solving in Constraint Programming by predicting effective nocrossing constraints" (Elena Bellodi, Alessandro Bertagnon, Marco ...

Posterior constraint optimal selection techniques (COSTs) are developed for nonnegative linear programming problems (NNLPs), and a geometric interpretation is provided. The posterior approach is used ...

It is also hard to find an optimal solution or at least high quality solutions. To solve this scheduling problem, we use the ¿expressive power¿ of the constraint programming paradigm to include as ...

According to IDC, the amount of data generated globally by 2025 would reach 175 zettabytes (~ 175 billion terabytes), a staggering 430 percent growth over the 33 zettabytes generated in 2018. The ...

Abstract: Constraint programming is used for a variety of real-world optimization problems, such as planning, scheduling, and resource allocation problems, all while we continuously gather vast ...