Manuel López-Ibáñez | DeepAI

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∙ 05/24/2023

Analysis of modular CMA-ES on strict box-constrained problems in the SBOX-COST benchmarking suite

Box-constraints limit the domain of decision variables and are common in...

0 Diederick Vermetten, et al. ∙

∙ 05/19/2023

Applying Ising Machines to Multi-objective QUBOs

Multi-objective optimisation problems involve finding solutions with var...

0 Mayowa Ayodele, et al. ∙

∙ 03/16/2023

Multi-Objective Archiving

Most multi-objective optimisation algorithms maintain an archive explici...

0 Miqing Li, et al. ∙

∙ 10/20/2022

A Study of Scalarisation Techniques for Multi-Objective QUBO Solving

In recent years, there has been significant research interest in solving...

0 Mayowa Ayodele, et al. ∙

∙ 09/09/2022

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

Algorithm selection wizards are effective and versatile tools that autom...

0 Risto Trajanov, et al. ∙

∙ 05/26/2022

Multi-objective QUBO Solver: Bi-objective Quadratic Assignment

Quantum and quantum-inspired optimisation algorithms are designed to sol...

0 Mayowa Ayodele, et al. ∙

∙ 04/20/2022

Analyzing the Impact of Undersampling on the Benchmarking and Configuration of Evolutionary Algorithms

The stochastic nature of iterative optimization heuristics leads to inhe...

10 Diederick Vermetten, et al. ∙

∙ 03/24/2022

Are Evolutionary Algorithms Safe Optimizers?

We consider a type of constrained optimization problem, where the violat...

0 Youngmin Kim, et al. ∙

∙ 01/25/2022

The First AI4TSP Competition: Learning to Solve Stochastic Routing Problems

This paper reports on the first international competition on AI for the ...

3 Laurens Bliek, et al. ∙

∙ 09/28/2021

Extensible Logging and Empirical Attainment Function for IOHexperimenter

In order to allow for large-scale, landscape-aware, per-instance algorit...

0 Johann Dréo, et al. ∙

∙ 02/05/2021

Reproducibility in Evolutionary Computation

Experimental studies are prevalent in Evolutionary Computation (EC), and...

0 Manuel López-Ibáñez, et al. ∙

∙ 01/23/2021

Safe Learning and Optimization Techniques: Towards a Survey of the State of the Art

Safe learning and optimization deals with learning and optimization prob...

0 Youngmin Kim, et al. ∙

∙ 07/07/2020

Benchmarking in Optimization: Best Practice and Open Issues

This survey compiles ideas and recommendations from more than a dozen re...

11 Thomas Bartz-Beielstein, et al. ∙

∙ 05/12/2020

Unified Framework for the Adaptive Operator Selection of Discrete Parameters

We conduct an exhaustive survey of adaptive selection of operators (AOS)...

8 Mudita Sharma, et al. ∙

∙ 05/20/2019

Deep Reinforcement Learning Based Parameter Control in Differential Evolution

Adaptive Operator Selection (AOS) is an approach that controls discrete ...

0 Mudita Sharma, et al. ∙

∙ 09/19/2014

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

The properties of local optimal solutions in multi-objective combinatori...

0 Manuel López-Ibáñez, et al. ∙

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