activity
20142024
most citedBenchmarking in Optimization: Best Practice and Open Issues

82 citations · 96 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2024

An adaptive approach to Bayesian Optimization with switching costs

Stefan Pricopie, Richard Allmendinger, Manuel Lopez-Ibanez +3

We investigate modifications to Bayesian Optimization for a resource-constrained setting of sequential experimental design where changes to certain design variables of the search s…

cs.NE2022★ 5 cited

Improving Nevergrad's Algorithm Selection Wizard NGOpt through Automated Algorithm Configuration

Risto Trajanov, Ana Nikolikj, Gjorgjina Cenikj +6

Algorithm selection wizards are effective and versatile tools that automatically select an optimization algorithm given high-level information about the problem and available compu…

cs.NE2021★ 1 cited

Extensible Logging and Empirical Attainment Function for IOHexperimenter

Johann Dreo, Manuel López-Ibáñez

In order to allow for large-scale, landscape-aware, per-instance algorithm selection, a benchmarking platform software is key. IOHexperimenter provides a large set of synthetic pro…

cs.NE2020★ 82 cited

Benchmarking in Optimization: Best Practice and Open Issues

Thomas Bartz-Beielstein, Carola Doerr, Daan van den Berg +14

This survey compiles ideas and recommendations from more than a dozen researchers with different backgrounds and from different institutes around the world. Promoting best practice…

cs.NE2020★ 3 cited

Unified Framework for the Adaptive Operator Selection of Discrete Parameters

Mudita Sharma, Manuel Lopez-Ibanez, Dimitar Kazakov

We conduct an exhaustive survey of adaptive selection of operators (AOS) in Evolutionary Algorithms (EAs). We simplified the AOS structure by adding more components to the framewor…

cs.NE2019

Deep Reinforcement Learning Based Parameter Control in Differential Evolution

Mudita Sharma, Alexandros Komninos, Manuel Lopez Ibanez +1

Adaptive Operator Selection (AOS) is an approach that controls discrete parameters of an Evolutionary Algorithm (EA) during the run. In this paper, we propose an AOS method based o…

cs.AI2014★ 5 cited

Local Optimal Sets and Bounded Archiving on Multi-objective NK-Landscapes with Correlated Objectives

Manuel López-Ibáñez, Arnaud Liefooghe, Sébastien Verel

The properties of local optimal solutions in multi-objective combinatorial optimization problems are crucial for the effectiveness of local search algorithms, particularly when the…