297 citations · 958 across the 50 of their papers we have counts for
5 papers · 1 filter
Analyzing the Impact of Undersampling on the Benchmarking and Configuration of Evolutionary Algorithms
Diederick Vermetten, Hao Wang, Manuel López-Ibañez +2
The stochastic nature of iterative optimization heuristics leads to inherently noisy performance measurements. Since these measurements are often gathered once and then used repeat…
Switching between Numerical Black-box Optimization Algorithms with Warm-starting Policies
Dominik Schröder, Diederick Vermetten, Hao Wang +2
When solving optimization problems with black-box approaches, the algorithms gather valuable information about the problem instance during the optimization process. This informatio…
IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics
Hao Wang, Diederick Vermetten, Furong Ye +2
Benchmarking and performance analysis play an important role in understanding the behaviour of iterative optimization heuristics (IOHs) such as local search algorithms, genetic and…
A Modular Hybridization of Particle Swarm Optimization and Differential Evolution
Rick Boks, Hao Wang, Thomas Bäck
In swarm intelligence, Particle Swarm Optimization (PSO) and Differential Evolution (DE) have been successfully applied in many optimization tasks, and a large number of variants,…
Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case
Diederick Vermetten, Hao Wang, Carola Doerr +1
One of the most challenging problems in evolutionary computation is to select from its family of diverse solvers one that performs well on a given problem. This algorithm selection…