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, ...

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 ...

Overview: Quantum AI combines quantum computing with artificial intelligence to solve complex problems beyond the reach of ...

Many engineering challenges come down to the same headache—too many knobs to turn and too few chances to test them. Whether tuning a power grid or designing a safer vehicle, each evaluation can be ...

The CMO role is evolving, blending data science with AI's unpredictability. Niva Bupa's Nimish Agrawal highlights the shift ...

Through the looking glass: In a field increasingly defined by quantum experiments and exotic materials, a physics team at Queen's University in Canada has shown that innovation can also come from the ...

Abstract: The manufacturing industry encounters numerous optimization problems, one of which is the optimization of storage location assignment (OSLA) problem in logistics. OSLA is a combinatorial ...

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

Want your business to show up in Google’s AI-driven results? The same principles that help you rank in Google Search still matter – but AI introduces new dimensions of context, reputation, and ...

KARLSRUHE, Germany and COLLEGE PARK, Md.– Kipu Quantum and IonQ (NYSE: IONQ) announced what they said is a record achievement: the successful solution of “the most complex known protein folding ...