Optimization problems rarely have a single right answer. In engineering design, scheduling, and machine learning, decision ...

Did a commonly used method for building evolutionary trees previously outperform newer approaches despite relying on less ...

Two of artificial intelligence’s most powerful yet fundamentally different tools are quietly merging, and a new open-access scientometric review has, for the first time, mapped exactly how fast, how b ...

Europe’s retail finance is shifting beyond apps as AI agents reshape interfaces and put greater focus on infrastructure, execution and governance.

Numerous real-world applications involve large-scale multi-objective optimization problems (LSMOPs) with hundreds or even thousands of decision variables. Although multi-objective evolutionary ...

Daniel Blumstein recently sat in a Colorado meadow waiting for yellow-bellied marmots to appear, as the ecologist and evolutionary biologist had done many times before, the New York Times reported.

For years, social media giants controlled what users saw in their feeds. While people could follow accounts, like posts or hide content they didn’t enjoy, recommendation algorithms controlled what was ...

Abstract: Multimodal multi-objective optimization problems (MMOPs) are prevalent in real-world applications and have emerged as a significant research focus in evolutionary computation. Unlike ...

Abstract: Efficient and safe path planning for multiple autonomous agents, such as unmanned aerial vehicles (UAVs), is essential in many real-world applications. The objective is to coordinate these ...

Individual sensor systems have limitations in the complex task of classifying shredded tobacco. This study aims to overcome these limitations by developing a novel evolutionary algorithm-based feature ...