Individual sensor systems have limitations in the complex task of classifying shredded tobacco. This study aims to overcome these limitations by developing a novel evolutionary algorithm-based feature ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

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 ...

A new evolutionary technique from Japan-based AI lab Sakana AI enables developers to augment the capabilities of AI models without costly training and fine-tuning processes. The technique, called ...

See /GLS/README.md for detailed documentation of this innovation. Population size: 200 Maximum generations: 300 Random mating probability (RMP): 0.4 Mutation rate: 0. ...

Abstract: This paper presents a learning-assisted evolutionary algorithm for energy-efficient dynamic task scheduling, simultaneously tackling processor allocation, task sequencing, and frequency ...

Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry ...

Abstract: This paper proposes a memory-enhanced evolutionary algorithm that can effectively address multi- and many-objective optimization problems with various Pareto fronts within a small number of ...

Google DeepMind’s AlphaEvolve Trains Itself to Create Advanced Algorithms Your email has been sent Google DeepMind has introduced AlphaEvolve, a generative AI agent designed to advance algorithms used ...