Abstract: Fully-supervised deep neural networks have achieved remarkable progress in medical image segmentation, yet they heavily rely on extensive manually labeled data and exhibit inflexibility for ...

This paper proposes an exact method to solve an integer indefinite quadratic bilevel problem with multiple objectives at the upper level, where the objective functions at both levels are a product 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 ...

Abstract: In this paper, we introduce a novel approach for addressing the multi-objective optimization problem in large language model merging via black-box multi-objective optimization algorithms.

Modern seismic codes ensure life safety, but code-compliant buildings can still suffer significant economic losses from earthquake-induced damage, even during moderate events. Performance-Based ...

This repository contains the code to run the experiments in the paper (Buckingham et al., 2025): Buckingham, J. M., Rojas Gonzalez, S., & Branke, J. (2025). Knowledge Gradient for Multi-Objective ...

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 ...