Solving complex optimization problems is central to many modern technologies, from logistics and financial modeling to chip ...

In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a consequence of global warming. These disasters cause billions of dollars in ...

Despite having tiny brains, bumblebees have demonstrated a remarkable ability to socially learn how to use tools, solve simple puzzles, and cooperate to achieve a goal. It seems they can also solve ...

In mid-May, OpenAI announced that an internal AI model had disproved the Erdős unit distance conjecture, a famous problem in discrete geometry that had stumped human mathematicians for the last 80 ...

1 Department of Applied Mathematical Sciences, Faculty of Computing, Engineering and Mathematical Sciences, Catholic University of Ghana, Sunyani, Ghana. 2 Department of Mathematics, School of ...

SLSQP stands for Sequential Least Squares Programming. It is a numerical optimization algorithm used to solve constrained nonlinear optimization problems. In this project, we aim to optimize objective ...

This paper presents a new three-term hybrid conjugate gradient projection method for handling large-scale convex-constrained nonlinear monotone equations that are prevalent in fields such as ...

You probably don’t need more time. By Jancee Dunn When I look back on all the major decisions I’ve dithered over, I could scream. It took me a decade to commit to becoming a parent. I wavered for a ...

Abstract: Recently, recurrent neural network (RNN) models have been extensively investigated for addressing time-dependent nonlinear optimization problems. However, few existing RNN models take ...