Yang Yongzhong presented management coordinates. In August 2025, Professor Yang Yongzhong published Blue Book on ...

Abstract: Problem transformation-based multiobjective evolutionary algorithms (MOEAs) face the risk of losing optimal solutions when transforming a large-scale multiobjective optimization problem into ...

Abstract: Over the past decades, extensive research has been conducted on adversarial attacks and defense mechanisms in deep learning, particularly in real-world applications such as autonomous ...

"Biologists have always been fascinated by strife and conflict, but cooperative exchanges, involving all species and networking large numbers of them into complex communities, are ubiquitous in the ...

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 ...

SCE-UA is a lightweight Python package implementing the Shuffled Complex Evolution (SCE-UA) algorithm for global optimization. Designed primarily for hydrological model calibration, it leverages NumPy ...

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 ...

Diffusion-Based Evolutionary Algorithms This repository contains the code of the work described in the following abstract. Abstract: This work explores the integration of denoising diffusion models ...