Abstract: This study proposes LiP-LLM: integrating linear programming and dependency graph with large language models (LLMs) for multi-robot task planning. For multi-robots to efficiently perform ...

Abstract: As one of the most critical components in modern LP solvers, presolve in linear programming (LP) employs a rich set of presolvers to remove different types of redundancy in input problems by ...

Have you ever wished Excel could just understand what you mean without endless tinkering with formulas or wrestling with messy data? That wish is no longer a distant dream. Microsoft’s new Excel AI ...

Doug Wintemute is a staff writer for Forbes Advisor. After completing his master’s in English at York University, he began his writing career in the higher education space. Over the past decade, Doug ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...

Mixed Integer Linear Programming (MILP) is essential for modeling complex decision-making problems but faces challenges in computational tractability and requires expert formulation. Current deep ...

Jessica Bradley explores the key differences between a linear economy and a circular economy, and looks at the latest business innovations in circularity. In recent years, there’s been growing ...

Linear programming (LP) solvers are crucial tools in various fields like logistics, finance, and engineering, due to their ability to optimize complex problems involving constraints and objectives.

Jeremy has more than 2200 published articles on Collider to his name, and has been writing for the site since February 2022. He's an omnivore when it comes to his movie-watching diet, so will gladly ...