This study presents the analysis and principle of an innovative optimizer named weIghted
meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean …

Vision-language models (VLMs) pre-trained on web-scale datasets have demonstrated
remarkable capabilities on downstream tasks when fine-tuned with minimal data. However …

This paper proposes a novel nature-inspired algorithm called Multi-Verse Optimizer (MVO).
The main inspirations of this algorithm are based on three concepts in cosmology: white …

This paper employs the recently proposed Grey Wolf Optimizer (GWO) for training Multi-
Layer Perceptron (MLP) for the first time. Eight standard datasets including five classification …

We consider approaches to brain dynamics and function that have been claimed to be
Darwinian. These include Edelman's theory of neuronal group selection, Changeux's theory …

Genetic algorithms have been used in science and engineering as adaptive algorithms for
solving practical problems and as computational models of natural evolutionary systems …

The ordering and orientation of genomic scaffolds to reconstruct chromosomes is an
essential step during de novo genome assembly. Because this process utilizes various …

This article gives a comprehensive introduction into one of the main branches of
evolutionary computation–the evolution strategies (ES) the history of which dates back to the …

Genetic algorithms (GAs) are a heuristic search and optimisation technique inspired by
natural evolution. They have been successfully applied to a wide range of real-world …

Metaheuristics are the most exciting development in approximate optimization techniques of
the last two decades. They have had widespread successes in attacking a variety of difficult …