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 ...

The R language for statistical computing has creeped back into the top 10 in Tiobe’s monthly index of programming language popularity. “Programming language R is known for fitting statisticians and ...

This is a graphical user interface (GUI) application built with Python and Tkinter, designed to solve linear programming problems using SciPy's optimization library (linprog). Generates a plot of the ...

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 ...

Looking to get into statistical programming but lack industry experience? We spoke with several statistical programmers from diverse backgrounds, and one thing became clear—there’s no single path to ...

From IDE plugins to external chatbots and running LLMs locally, these new and emerging tools are bringing the generative AI revolution to R. My previous article focused on some of the best tools for ...

How to solve linear programming and quadratic programming with inequality constraint only? For LP, I tried to use OSQP and pass the objective as (None, -c), the equality constraint as (None, None), ...

In MarTech’s “MarTechBot explains it all” feature, we pose a question about marketing to our very own MarTechBot, which is trained on the MarTech website archives and has access to the broader ...

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 ...

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 ...