When to be Discrete: Analyzing Algorithm Performance on Discretized
Continuous Problems

When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems

25 April 2023

André Thomaser

Diederick Vermetten

Thomas Bäck

Anna V. Kononova

Papers citing "When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems"

5 / 5 papers shown

Title
CMA-ES with Margin: Lower-Bounding Marginal Probability for Mixed-Integer Black-Box Optimization Ryoki Hamano Shota Saito Masahiro Nomura Shinichi Shirakawa 28 35 0 26 May 2022
IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics Hongya Wang Diederick Vermetten Furong Ye Carola Doerr Thomas Bäck 94 48 0 08 Jul 2020
Benchmarking in Optimization: Best Practice and Open Issues Thomas Bartz-Beielstein Carola Doerr Daan van den Berg Jakob Bossek Sowmya Chandrasekaran ... B. Naujoks Patryk Orzechowski Vanessa Volz Markus Wagner T. Weise 87 112 0 07 Jul 2020
The CMA Evolution Strategy: A Tutorial N. Hansen 69 1,372 0 04 Apr 2016
CMA-ES with Two-Point Step-Size Adaptation Nikolaus Hansen 114 575 0 02 May 2008