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06/30/2023
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems
Performance complementarity of solvers available to tackle black-box opt...
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06/29/2023
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms
The L_∞ star discrepancy is a measure for the regularity of a finite set...
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06/18/2023
MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts
Extending a recent suggestion to generate new instances for numerical bl...
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05/31/2023
Assessing the Generalizability of a Performance Predictive Model
A key component of automated algorithm selection and configuration, whic...
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05/24/2023
Challenges of ELA-guided Function Evolution using Genetic Programming
Within the optimization community, the question of how to generate new o...
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05/24/2023
Analysis of modular CMA-ES on strict box-constrained problems in the SBOX-COST benchmarking suite
Box-constraints limit the domain of decision variables and are common in...
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04/25/2023
When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems
The domain of an optimization problem is seen as one of its most importa...
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03/08/2023
Using Affine Combinations of BBOB Problems for Performance Assessment
Benchmarking plays a major role in the development and analysis of optim...
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02/17/2023
To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features
Dynamic algorithm selection aims to exploit the complementarity of multi...
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02/02/2023
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler
Submodular functions play a key role in the area of optimization as they...
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01/24/2023
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms
Empirical data plays an important role in evolutionary computation resea...
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11/29/2022
BBOB Instance Analysis: Landscape Properties and Algorithm Performance across Problem Instances
Benchmarking is a key aspect of research into optimization algorithms, a...
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04/20/2022
Per-run Algorithm Selection with Warm-starting using Trajectory-based Features
Per-instance algorithm selection seeks to recommend, for a given problem...
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04/20/2022
Analyzing the Impact of Undersampling on the Benchmarking and Configuration of Evolutionary Algorithms
The stochastic nature of iterative optimization heuristics leads to inhe...
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04/15/2022
The Importance of Landscape Features for Performance Prediction of Modular CMA-ES Variants
Selecting the most suitable algorithm and determining its hyperparameter...
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04/13/2022
Chaining of Numerical Black-box Algorithms: Warm-Starting and Switching Points
Dynamic algorithm selection can be beneficial for solving numerical blac...
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04/13/2022
Trajectory-based Algorithm Selection with Warm-starting
Landscape-aware algorithm selection approaches have so far mostly been r...
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11/07/2021
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics
We present IOHexperimenter, the experimentation module of the IOHprofile...
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09/20/2021
Benchmarking the Status of Default Pseudorandom Number Generators in Common Programming Languages
The ever-increasing need for random numbers is clear in many areas of co...
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05/10/2021
Is there Anisotropy in Structural Bias?
Structural Bias (SB) is an important type of algorithmic deficiency with...
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04/24/2021
OPTION: OPTImization Algorithm Benchmarking ONtology
Many platforms for benchmarking optimization algorithms offer users the ...
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02/25/2021
Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules
Introducing new algorithmic ideas is a key part of the continuous improv...
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12/15/2020
Squirrel: A Switching Hyperparameter Optimizer
In this short note, we describe our submission to the NeurIPS 2020 BBO c...
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07/08/2020
IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic
We propose IOHanalyzer, a new software for analyzing the empirical perfo...
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06/11/2020
Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case
One of the most challenging problems in evolutionary computation is to s...
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12/12/2019
Sequential vs. Integrated Algorithm Selection and Configuration: A Case Study for the Modular CMA-ES
When faced with a specific optimization problem, choosing which algorith...
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04/16/2019
