Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...

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This repository contains a collection of prototype linear programming (LP) applications that implement specific algorithms I learned in college. The purpose is to demonstrate that these mathematical ...

Chemical Physics Theory Group, Department of Chemistry, University of Toronto, Toronto, Ontario, Canada M5S 3H6 Department of Physical and Environmental Sciences, University of Toronto Scarborough, ...

ABSTRACT: This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two ...

NVIDIA's cuOpt leverages GPU technology to drastically accelerate linear programming, achieving performance up to 5,000 times faster than traditional CPU-based solutions. The landscape of linear ...

Many important practical computations, such as scheduling, combinatorial, and optimization problems, use techniques known as integer programming to find the best combination of many variables. In ...