If Python developers have one consistent gripe about their beloved language, it tends to be this: Why is it so hard to take a Python program and deploy it as a ...

We consider the optimal scheduling of hydropower plants in a hydrothermal interconnected system. This problem, of outmost importance for large-scale power systems with a high proportion of hydraulic ...

In the era of A.I. agents, many Silicon Valley programmers are now barely programming. Instead, what they’re doing is deeply, deeply weird. Credit...Illustration by Pablo Delcan and Danielle Del Plato ...

Abstract: In this paper, we propose a parallel shooting algorithm for solving nonlinear model predictive control problems using sequential quadratic programming. This algorithm is built on a two-phase ...

Many practical applications can be formulated as time-varying quadratic programming (TVQP) problems. Improving solution speed and accuracy can theoretically enhance efficiency. However, existing ...

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A new way to compute the English Language Mathematical Model (ELMM) is described in this paper using a neural network hybridized with a genetic algorithm-based Sequential Quadratic Programming (SQP) ...

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Optimization is a crucial tool throughout science and technology. Large datasets and high dimensional problems create unique challenges for standard optimization techniques such as Newton’s method, ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Programming is a key transferable skill within the chemical sciences with applications ...

One way to speed up your Python programs is to write modules in the Zig language and use them in your Python code. Here's how to get started. Python might not be the fastest of languages, but it has ...