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

To address the conflict issues among structural mass, maximum deformation, and equivalent stress in traditional lightweight design of aircraft structures, and to improve optimization efficiency while ...

Luke Fox: The goal of using the genetic algorithm was to create an optimal massing that prioritized the creation of a central public square and maximized views for the building's occupants.

Aiming at the unsmooth path planning problem of four-wheel intelligent vehicle path planning algorithm, this article proposed an improved genetic and ant colony hybrid algorithm, and the physical ...

After that, Section 3 presents the power flow optimization model of systems with PST. Next, Section 4 describes the data-driven approach used to replace the traditional PF calculation and highlights ...

Scheduling problem is a multi-objective optimization problem. Genetic algorithms (GAs) have showed the ability of finding near optimal solutions for flow-shop scheduling problems. The infection of ...