Multi-objective optimisation using evolutionary algorithms constitutes a powerful computational framework that addresses complex problems involving conflicting objectives.

In the new era, the Internet of Everything (IoE) provides distributed services like data, processes, people, and things, etc. The services to the connected IoE significantly increase the time of ...

As cities worldwide begin embracing low-altitude logistics to support rapid, flexible deliveries by drones, urban planners face an increasingly ...

Expensive constrained multi-objective optimization problems (ECMOPs) present a significant challenge to surrogate-assisted evolutionary algorithms (SAEAs) in effectively balancing optimization of the ...

Aqarios' platform Luna v1.0 marks a major milestone in quantum optimization. This release significantly improves usability, ...

Alignment and sequencing errors are a major concern in molecular evolution, and this valuable study represents a welcome improvement for genome-wide scans of positive selection. This new method seems ...

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A research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has proposed a novel model optimization algorithm—External Calibration-Assisted Screening (ECA)— that ...

A team of researchers has developed a method that could transform the field of protein engineering. The new approach, called ...

A single β-lactam exposure rapidly drives stable multidrug resistance in RecA-deficient bacteria through an SOS-independent mechanism involving oxidative stress-induced mutagenesis and ...