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 stared at a sprawling Excel spreadsheet, wondering how to make sense of the chaos? For many, Excel formulas feel like a secret language, powerful yet elusive. But here’s the truth: ...

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 ...

A new study published in the journal Cyberpsychology, Behavior, and Social Networking has shed light on why some people have intrusive thoughts and obsessive concerns about their romantic ...

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 ...

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.