When natural disasters or extreme weather events hit, delivering aid quickly and efficiently to those affected is crucial. Humanitarian relief efforts commonly rely on the combination of trucks and ...

Abstract: Solving constrained multi-objective optimization problems (CMOPs) is a challenging task due to the presence of multiple conflicting objectives and intricate constraints. In order to better ...

Most of you have used a navigation app like Google Maps for your travels at some point. These apps rely on algorithms that ...

In a new study, scientists successfully trained a brain organoid derived from mouse stem cells to solve an engineering benchmark known as the “cart-pole problem.” By applying weak or strong electric ...

Transportation to and from work is a real issue for many in York County and Southcentral Pennsylvania. A new commuter vanpool service was unveiled Tuesday, Feb. 24, to bridge the gap to help eliminate ...

Abstract: Surrogate-assisted evolutionary algorithms (SAEAs) have been widely developed to solve complex and computationally expensive multiobjective optimization problems (EMOPs) in recent years.