Amoeba-inspired method could enable energy-efficient hardware for complex optimization

Дата публикации: 26-08-2026 15:40:07

Combinatorial optimization problems are ubiquitous, underpinning decision-making in a wide range of fields, including logistics, transportation, communication networks, drug discovery and materials science. However, these problems are computationally expensive, especially for conventional computing systems. As a result, researchers are exploring new computing paradigms capable of solving such problems more efficiently.

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