Abstract: This article proposes a novel constrained multiobjective evolutionary Bayesian optimization algorithm based on decomposition (named CMOEBO/D) for expensive constrained multiobjective ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In this paper, we introduce a methodology to improve upon the ...

When we first land in the Codex environment, it feels like stepping into a co-pilot’s seat for coding. Codex is designed to take over much of the routine or overwhelming parts of software engineering, ...

Background and objective: The increasing global prevalence of diabetes has led to a surge in complications, significantly burdening healthcare systems and affecting patient quality of life. Early ...

1 Department of Civil Engineering, King Saud University, Riyadh, Saudi Arabia 2 Department of Civil, Materials, and Environmental Engineering, The University of Illinois Chicago, Chicago, IL, United ...

Even those with the disorder can’t always spot misleading posts, a study finds. By Christina Caron On TikTok, misinformation about attention deficit hyperactivity disorder can be tricky to spot, ...

The rapid advancement of Large Language Models (LLMs) has significantly improved their ability to generate long-form responses. However, evaluating these responses efficiently and fairly remains a ...

Abstract: Bayesian optimization (BO) is a framework for global optimization of expensive-to-evaluate objective functions. Classical BO methods assume that the objective function is a black box.

A hybrid strategy is proposed to solve the problems of poor population diversity, insufficient convergence accuracy and susceptibility to local optimal values in the original Arctic Puffin ...