Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization
In this survey, we introduce Meta-Black-Box-Optimization (MetaBBO) as an emerging
avenue within the Evolutionary Computation (EC) community, which incorporates Meta …
avenue within the Evolutionary Computation (EC) community, which incorporates Meta …
Synergies of deep and classical exploratory landscape features for automated algorithm selection
Per-instance automated algorithm selection (AAS) aims at leveraging the complementarity of
optimization algorithms with respect to different problem types. State-of-the-art AAS methods …
optimization algorithms with respect to different problem types. State-of-the-art AAS methods …
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization
The recently proposed MA-BBOB function generator provides a way to create numerical
black-box benchmark problems based on the well-established BBOB suite. Initial studies on …
black-box benchmark problems based on the well-established BBOB suite. Initial studies on …
A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization
The selection of the most appropriate algorithm to solve a given problem instance, known as
algorithm selection, is driven by the potential to capitalize on the complementary …
algorithm selection, is driven by the potential to capitalize on the complementary …
Learned Features vs. Classical ELA on Affine BBOB Functions
Automated algorithm selection has proven to be effective to improve optimization
performance by using machine learning to select the best-performing algorithm for the …
performance by using machine learning to select the best-performing algorithm for the …
Impact of spatial transformations on landscape features of CEC2022 basic benchmark problems
When benchmarking optimization heuristics, we need to take care to avoid an algorithm
exploiting biases in the construction of the used problems. One way in which this might be …
exploiting biases in the construction of the used problems. One way in which this might be …
A Deep Dive Into Effects of Structural Bias on CMA-ES Performance Along Affine Trajectories
To guide the design of better iterative optimisation heuristics, it is imperative to understand
how inherent structural biases within algorithm components affect the performance on a …
how inherent structural biases within algorithm components affect the performance on a …