Aug 30, 2023 · The objective of this work is to develop a method for generating benchmark functions for single-objective continuous optimization with user-specified ...

Sep 1, 2023 · They used exploratory land- scape analysis (ELA) [24] to test how diverse each of these functions really is w.r.t. a subset of ELA features.

These problem instances are structured in problem benchmark suites, the most commonly used ones being the Black Box Optimization Benchmarking (BBOB) [4] ...

Aug 30, 2023 · The objective of this work is to develop a method for generating benchmark functions for single-objective continuous optimization with user- ...

Aug 20, 2024 · Recent research in Meta-Black-Box Optimization (MetaBBO) have shown that meta-trained neural networks can effectively guide the design of black- ...

Sep 25, 2024 · The paper introduces Neural Exploratory Landscape Analysis (NeurELA), a novel framework designed to improve Meta-Black-Box Optimization (MetaBBO) ...

"Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features" Proceedings of the 17th ACM/SIGEVO Conference on Foundations ...

Olaf Mersmann's 51 research works with 2063 citations, including: Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape ...

Sep 2, 2024 · Unlike the well understood BBOB functions, the landscape characteristics and global optimum of RGF are not known a priori. Due to the fact that ...

Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization Problems.