Abstract: Solving constrained multi-objective optimization problems (CMOPs) involves simultaneously achieving convergence to the Pareto front, preserving solution diversity, and satisfying complex ...

A team of researchers from the Shanghai Institute of Applied Physics, Chinese Academy of Sciences, has developed an ...

The challenge of resource allocation for UAV swarms in dynamic and uncertain electromagnetic environments has been investigated for years. In a recent breakthrough published in the Chinese Journal of ...

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 ...

Tourism development in emerging destinations requires balancing economic benefits with ecological sustainability. In this study, we investigate the case of multi-attraction tourism planning in Qujing ...

High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...

Abstract: To address the challenge of rapidly tracking the new pareto optimal set (PS) after environmental changes in dynamic multi-objective optimization problems (DMOPs), this paper proposes a ...

In the fast-evolving field of electronic systems design, engineers are under increasing pressure to deliver innovative, high-performance products within ever ...

This repository implement MFEA-II MFEA-II Official Matlab Version. Tested on MTSOO benchmark. This repo could be used as a template or starter code for conducting multitasking optimization on other ...