Search Results for author: Sander van Rijn

Found 4 papers, 1 papers with code

Online Selection of CMA-ES Variants

no code implementations16 Apr 2019 Diederick Vermetten, Sander van Rijn, Thomas Bäck, Carola Doerr

An analysis of module activation indicates which modules are most crucial for the different phases of optimizing each of the 24 benchmark problems.

IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics

5 code implementations11 Oct 2018 Carola Doerr, Hao Wang, Furong Ye, Sander van Rijn, Thomas Bäck

Given as input algorithms and problems written in C or Python, it provides as output a statistical evaluation of the algorithms' performance by means of the distribution on the fixed-target running time and the fixed-budget function values.

Benchmarking

Towards a Theory-Guided Benchmarking Suite for Discrete Black-Box Optimization Heuristics: Profiling $(1+λ)$ EA Variants on OneMax and LeadingOnes

no code implementations17 Aug 2018 Carola Doerr, Furong Ye, Sander van Rijn, Hao Wang, Thomas Bäck

Marking an important step towards filling this gap, we adjust the COCO software to pseudo-Boolean optimization problems, and obtain from this a benchmarking environment that allows a fine-grained empirical analysis of discrete black-box heuristics.

Benchmarking Evolutionary Algorithms

Evolving the Structure of Evolution Strategies

no code implementations17 Oct 2016 Sander van Rijn, Hao Wang, Matthijs van Leeuwen, Thomas Bäck

Various variants of the well known Covariance Matrix Adaptation Evolution Strategy (CMA-ES) have been proposed recently, which improve the empirical performance of the original algorithm by structural modifications.

Cannot find the paper you are looking for? You can Submit a new open access paper.