This approach can be viewed as a memory plug-in for large models, providing a fresh perspective and direction for solving the ...

Abstract: An increasing number of machine learning algorithms are being applied to multi-objective optimization problems (MOPs), yielding promising results. However, many of these algorithms suffer ...

New design, verification and simulation solutions to re-engineer AI-powered product innovation at Synopsys Converge 2026.

Abstract: In recent years, many multimodal multi-objective evolutionary algorithms (MMOEAs) have been proposed for the widely existing multimodal multi-objective optimization problems (MMOPs) in ...

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 ...

Google's second generation of its AI mathematics system combines a language model with a symbolic engine to solve complex geometry problems better than International Mathematical Olympiad (IMO) gold ...