In art, brush marks can be seen as a flaw or the signature of a noted painter. Similarly, what appears to be operational ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

AUSTIN, Texas and TOKYO, Dec. 29, 2025 /PRNewswire/ -- According to DataM Intelligence, the Quantum Computing in Financial ...

My graduate studies included learning about constraint-based optimization algorithms (such as linear programming) and ...

A hybrid geothermal–biomass system integrates multigeneration heating, cooling, and power through thermodynamic and economic optimization.

The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get ...

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 ...

Abstract: Evolutionary algorithms have been proven effective in solving complex optimization problems. This paper proposes a production shape optimization framework, and a data-driven and ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...

Abstract: In this article, the distributed form of the zeroing neural network for solving time-varying optimal problems is put forward. Compared with traditional centralized algorithms, distributed ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...