Convex Optimization and Feasibility Problems Publication Trend The graph below shows the total number of publications each year in Convex Optimization and Feasibility Problems.

This paper introduces a class of discrete-time distributed online optimization algorithms, with a group of agents whose communication topology is given by a uniformly strongly connected sequence of ...

Convex optimization solvers are widely used in the embedded systems that require sophisticated optimization algorithms including model predictive control (MPC). In this paper, we aim to reduce the ...

Aqarios' platform Luna v1.0 marks a major milestone in quantum optimization. This release significantly improves usability, ...

Supply chains consist of imperfect humans struggling to make perfect decisions. In the end, though, it all comes down to a game of numbers.

A new AI model learns to "think" longer on hard problems, achieving more robust reasoning and better generalization to novel, unseen tasks.

A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and ...

A research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has proposed a novel model optimization algorithm—External Calibration-Assisted Screening (ECA)— that ...

Goal 2 is about creating a world free of hunger by 2030.The global issue of hunger and food insecurity has shown an alarming increase since 2015, a trend exacerbated by a combination of factors ...

Discover how to avoid the trap of endless optimization in education and daily life—focus on depth, not constant tweaking.