Optimization algorithms and metaheuristics constitute a vital area of computational science, offering robust strategies for tackling complex, multidimensional problems across diverse domains. These ...

In the lower part of the figure, it can be seen that L2O leverages on a set of training problem instances from the target optimization problem class to gain knowledge. This knowledge can help identify ...

The development of vehicle components is a lengthy and therefore very costly process. Researchers have developed a method that can shorten the development phase of the powertrain of battery electric ...

Practical Application: The authors propose QFI-Informed Mutation (QIm), a heuristic that adapts mutation probabilities using diagonal QFI entries. QIm outperforms uniform and random-restart baselines, ...

Incorporating multiple constraints such as task completion time, UAV payload capacity, and flight range into path optimization algorithms allows for more efficient search patterns.

In large retail operations, category management teams spend significant time deciding which product goes onto which shelf and in which order. Shelf space is very expensive real estate in retail.

Many experts believe that once quantum computers are big enough and reliable enough to solve useful problems, the most common deployment architecture will be to have them serve as accelerators for ...

Search behavior keeps evolving, and algorithms follow closely behind. In 2026, ranking success depends less on isolated ...