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 ...

1 Guangzhou Institute of Building Science Group Co., Ltd., Guangzhou, Guangdong, China 2 Glenn Department of Civil Engineering, Clemson University, Clemson, SC, United States Modern seismic codes ...

Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan Graduate School of Science and Technology, Nara Institute of ...

Search optimization now requires combining traditional SEO with AI-focused GEO and answer-driven AEO strategies AI search usage continues to grow, with 10% of US consumers currently using generative ...

1 School of Mathematics and Statistics, Sichuan University of Science and Engineering, Zigong, China. 2 Institute of Computational Mathematics and Scientific/Engineering Computing, Chinese Academy of ...

Abstract: This paper addresses multi-objective optimization problems using conflict-averse multi-objective extremum seeking (CAMOES) for unknown static mapping. As for the traditional multi-objective ...

Part of the joy of watching Jon M. Chu’s “Wicked” is getting to witness Elphaba (Cynthia Erivo) as she comes to realize her true purpose: doing everything in her (magical) power to free the animals of ...

Abstract: In order to improve the rationality of integrated energy system (IES) scheduling strategy and promote carbon reduction planning, this paper proposes a multi-objective optimization scheduling ...

You make decisions every day. Some are big, and some are small. But even the small decisions involve a great deal of complexity. Let me show you what I mean. Take something you probably do regularly: ...

Multiobjective optimization (MOO) is pivotal in machine learning, enabling researchers to balance multiple conflicting objectives in real-world applications. These applications include robotics, fair ...