When robots and autonomous systems break down in production, the cost can be millions of dollars and real safety risk.

Cost optimization that strives to minimize spending has long been the norm. But conventional wisdom doesn't always apply in the digital era.

In next-generation silicon, AI can interpret system behavior at scale, but only if observability is designed into the fabric ...

Founded by Kelsey Woody, Ari Rewards celebrates its official launch as a data-driven travel platform designed to help modern ...

From affordability to carbon output, there are many reasons to bring topological optimization out of the realm of 3D printing ...

At the recent Data Center World 2026 in Washington, D.C., one message came through louder than ever: AI infrastructure is ...

In 2022, global production of construction materials accounted for more than 7% of total carbon emissions. But how many of ...

Abstract: Multiobjective optimization is increasingly used in engineering to design new systems and to identify design tradeoffs. Yet, design problems often have objective functions and constraints ...

SBArchOpt (es-bee-ARK-opt) provides a set of classes and interfaces for applying Surrogate-Based Optimization (SBO) for system architecture optimization problems: Expensive black-box problems: ...

In the field of evolutionary computation, it is common to compare different algorithms using a large test set, especially when the test involves function optimization [GW93]. However, the ...

Abstract: In this paper, optimum design of engineering problems is considered by means of the Atomic Orbital Search (AOS), a recently proposed metaheuristic optimization algorithm. The mathematical ...