Solving complex optimization problems is central to many modern technologies, from logistics and financial modeling to chip ...

Abstract: Over the last three decades, a large number of evolutionary algorithms have been developed for solving multi-objective optimization problems. However, there lacks an upto-date and ...

The automation waves of the past rewarded companies with the best systems, not the most robots, and AI will be no different.

A math whiz as a young man, he later blazed trails, both with his theoretical advances and his advocacy for minority students.

Tensor networks enable researchers to tackle quantum physics problems previously thought to be solvable only by quantum computers. Credit: Lucy Reading-Ikkanda/Simons Foundation By applying a 1980s ...

Abstract: For various daunting physical world structural optimization design problems, a novel multi-objective water strider algorithm (MOWSA) is proposed, and its non-dominated sorting (NDS) ...

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The result is correct but challenges core norms of mathematics: checking proofs, crediting ideas and keeping research open to everyone.

Decades ago, Paul Erdős used randomness to illuminate the vast and weird world of networks. Now mathematicians are making his ...

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