19 citations · 22 across the 19 of their papers we have counts for
6 papers · 2 filters
Integer Natural Evolution Strategies
Jacob de Nobel, Diederick Vermetten, Hao Wang +3
While contemporary Evolution Strategies handle integer optimization problems effectively, their adaptation mechanism is grounded in -based Gaussian models, which are not na…
Sampling on Random Subspaces under Limited Data in the Context of Exploratory Landscape Analysis
Iván Olarte Rodríguez, Anja Jankovic, Thomas Bäck +1
Classical space-filling designs often fail to provide reliable statistical results for Exploratory Landscape Analysis (ELA) when only limited evaluation budgets are available, as c…
LLM-Driven Evolutionary Generation of Multi-Objective Bayesian Optimization Algorithms
Georgios Laskaris, Reuben Brasher, Niki van Stein +3
Designing effective multi-objective Bayesian optimization (MOBO) algorithms requires balancing many interdependent design choices whose optimal configuration is problem-dependent a…
Block-Bench: A Framework for Controllable and Transparent Discrete Optimization Benchmarking
Furong Ye, Frank Neumann, Thomas Bäck +1
We present a novel approach for constructing discrete optimization benchmarks that enables fine-grained control over problem properties, and such benchmarks can facilitate analyzin…
Optimization is Not Enough: Why Problem Formulation Deserves Equal Attention
Iván Olarte Rodríguez, Gokhan Serhat, Mariusz Bujny +3
Black-box optimization is increasingly used in engineering design problems where simulation-based evaluations are costly and gradients are unavailable. In this context, the optimiz…
Investigating the Interplay of Parameterization and Optimizer in Gradient-Free Topology Optimization: A Cantilever Beam Case Study
Jelle Westra, Iván Olarte Rodríguez, Niki van Stein +2
Gradient-free black-box optimization (BBO) is widely used in engineering design and provides a flexible framework for topology optimization (TO), enabling the discovery of high-per…