ACCEPTED PAPERS
The following is the list of the 99 accepted papers out of 268 submitted papers. You can find the poster paintings here.
Multi-Fidelity Optimization Approach under Prior and Posterior Constraints and its Application to Compliance Minimization
Youhei Akimoto, Naoki Sakamoto, and Makoto Ohtani
The Hessian Estimation Evolution Strategy
Tobias Glasmachers and Oswin Krause
Global Landscape Structure and the Random MAX-SAT Phase Transition
Gabriela Ochoa, Francisco Chicano, and Marco Tomassini
Large Population Sizes and Crossover Help in Dynamic Environments
Johannes Lengler and Jonas Meier
An Ensemble Indicator-based Density Estimator for Evolutionary Multi-Objective Optimization
Jesús Guillermo Falcón-Cardona, Arnaud Liefooghe, and Carlos A. Coello Coello
Improved Fixed Budget Results via Drift Analysis
Timo Kötzing and Carsten Witt
Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy
Quentin Renau, Carola Doerr, Johann Dreo, and Benjamin Doerr
Visualising Evolution History in Multi- and Many-Objective Optimisation
Mathew J. Walter, David J. Walker, and Matthew J. Craven
Analysis on the Efficiency of Multifactorial Evolutionary Algorithms
Zhengxin Huang, Zefeng Chen, and Yuren Zhou
Improving Imbalanced Classification by Anomaly Detection
Jiawen Kong, Wojtek Kowalczyk, Stefan Menzel, and Thomas Bäck
Adaptive Operator Selection Based on Dynamic Thompson Sampling for MOEA/D
Lei Sun and Ke Li
Human-Like Summaries from Heterogeneous and Time-Windowed Software Development Artefacts
Mahfouth Alghamdi, Christoph Treude, and Markus Wagner
Continuous Optimization Benchmarks by Simulation
Martin Zaefferer and Frederik Rehbach
Decentralized Combinatorial Optimization
Lee A. Christie
Evolved Gossip Contracts – A Framework for designing Multi-agent Systems
Nicola Mc Donnell, Enda Howley, and Jim Duggan
Image Feature Learning with Genetic Programming
Stefano Ruberto, Valerio Terragni, and Jason H. Moore
Exponential Upper Bounds for the Runtime of Randomized Search Heuristics
Benjamin Doerr
Evolving Deep Forest with Automatic Feature Extraction for Image Classification Using Genetic Programming
Ying Bi, Bing Xue and Mengjie Zhang
Hypervolume Optimal μ-Distributions on Line-based Pareto Fronts in Three Dimensions
Ke Shang, Hisao Ishibuchi, Weiyu Chen, and Lucáš Adam
A Variable Neighborhood Search for the Job Sequencing with One Common and Multiple Secondary Resources Problem
Thomas Kaufmann, Matthias Horn, and Günther R. Raidl
Fast Perturbative Algorithm Configurators
George T. Hall, Pietro S. Oliveto and Dirk Sudholt.
Solution Repair by Inequality Network Propagation in LocalSolver
Léa Blaise, Christian Artigues, and Thierry Benoist
The Usability Argument for Refinement Typed Genetic Programming
Alcides Fonseca, Paulo Santos, and Sara Silva
Model-Based Algorithm Configuration with Default-Guided Probabilistic Sampling
Marie Anastacio and Holger Hoos
Behavior Optimization in Large Distributed Systems Modeled by Cellular Automata
Franciszek Seredyński and Jakub Gąsior
Parallelized Bayesian Optimization for Expensive Robot Controller Evolution
Margarita Rebolledo, Frederik Rehbach, A.E. Eiben, and Thomas Bartz-Beielstein
Evolutionary Algorithms with Self-adjusting Asymmetric Mutation
Amirhossein Rajabi and Carsten Witt
On averaging the best samples in evolutionary computation
Laurent Meunier, Yann Chevaleyre, Jeremy Rapin, Clément H. Royer, and Olivier Teytaud
Variance Reduction for Better Sampling in Continuous Domains
Laurent Meunier, Carola Doerr, Jeremy Rapin, and Olivier Teytaud
Network Representation Learning based on Topological Structure and Vertex Attributes
Shengxiang Hu, Bofeng Zhang, Ying Lv, Furong Chang, and Zhuocheng Zhou
Multi-Objective Counterfactual Explanations
Susanne Dandl, Christoph Molnar, Martin Binder, and Bernd Bischl
PbO-CCSAT: Boosting Local Search for Satisfiability using Programming by Optimisation
Chuan Luo, Holger Hoos and Shaowei Cai
Evolutionary Multi-Objective Design of SARS-CoV-2 Protease Inhibitor Candidates
Tim Cofala, Lars Elend, Philip Mirbach, Jonas Prellberg, Thomas Teusch, and Oliver Kramer
Designing Air Flow with Surrogate-assisted Phenotypic Niching
Alexander Hagg, Dominik Wilde, Alexander Asteroth, and Thomas Bäck
Learning Step-Size Adaptation in CMA-ES
Gresa Shala, André Biedenkapp, Noor Awad, Steven Adriaensen, Marius Lindauer, and Frank Hutter.
Comparative Run-Time Performance of Evolutionary Algorithms on Multi-Objective Interpolated Continuous Optimization Problems
Alexandru-Ciprian Zăvoianu, Benjamin Lacroix, and John McCall
Towards Novel Meta-heuristic Algorithms for Dynamic Capacitated Arc Routing Problems
Hao Tong, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, and Xin Yao
Evolving Sampling Strategies for One-Shot Optimization Tasks
Jakob Bossek, Carola Doerr, Pascal Kerschke, Aneta Neumann, and Frank Neumann
Canonical Correlation Discriminative Learning for Domain Adaptation
Wenjing Wang, Yuwu Lu, and Zhihui Lai
Maximizing Submodular or Monotone Functions under Partition Matroid Constraints by Multi-objective Evolutionary Algorithms
Anh Viet Do and Frank Neumann
Multi-objective Optimization by Uncrowded Hypervolume Gradient Ascent
Timo M. Deist, Stefanus C. Maree, Tanja Alderliesten, and Peter A. N. Bosman
One PLOT to Show Them All: Visualization of Efficient Sets in Multi-Objective Landscapes
Lennart Schäpermeier, Christian Grimme, and Pascal Kerschke
Many-objective Test Database Generation for SQL
Zhilei Ren, Shaozheng Dong, Xiaochen Li, Zonzheng Chi, and He Jiang
On Sharing Information betweenSub-populations in MOEA/S
Lucas de Almeida Ribeiro, Michael Emmerich, Anderson Da Silva Soares, and Telma Woerle de Lima
Can compact optimisation algorithms be structurally biased?
Anna V. Kononova, Fabio Caraffini, Hao Wang and Thomas Bäck
Sparse Inverse Covariance Learning for CMA-ES with Graphical Lasso
Konstantinos Varelas, Anne Auger, and Nikolaus Hansen
Simple Surrogate Model Assisted Optimization with Covariance Matrix Adaptation
Lauchlan Toal and Dirk V. Arnold
Robust evolutionary bi-objective optimization for prostate cancer treatment with high-dose-rate brachytherapy
Marjolein C. van der Meer, Arjan Bel, Yury Niatsetski, Tanja Alderliesten, Bradley R. Pieters, and Peter A.N. Bosman
Ensuring smoothly navigable approximation sets by Bézier curve parameterizations in evolutionary bi-objective optimization
Stefanus C. Maree, Tanja Alderliesten, and Peter A.N. Bosman
Hybridizing the 1/5-th Success Rule with Q-Learning for Controlling the Mutation Rate of an Evolutionary Algorithm
Arina Buzdalova, Carola Doerr, and Anna Rodionova
BACS: A Thorough Study of Using Behavioral Sequences in ACS2
Romain Orhand, Anne Jeannin-Girardon, Pierre Parrend, and Pierre Collet
Dominance, Indicator and Decomposition based Search for Multi-objective QAP: Landscape Analysis and Automated Algorithm Selection
Arnaud Liefooghe, Sébastien Verel, Bilel Derbel, Hernan Aguirre, and Kiyoshi Tanaka
A Permutational Boltzmann Machine with Parallel Tempering for Solving Combinatorial Optimization Problems
Mohammad Bagherbeik, Parastoo Ashtari, Seyed Farzad Mousavi, Kouichi Kanda, Hirotaka Tamura, and Ali Sheikholeslami
A SHADE-Based Algorithm for Large Scale Global Optimization
Oscar Pacheco-Del-Moral and Carlos A. Coello Coello
Lower Bounds for Non-Elitist Evolutionary Algorithms via Negative Multiplicative Drift
Benjamin Doerr
Optimising Chance-Constrained Submodular Functions Using Evolutionary Multi-Objective Algorithms
Aneta Neumann and Frank Neumann
A Study of Swarm Topologies and Their Influence on the Performance of Multi-Objective Particle Swarm Optimizers
Diana Cristina Valencia-Rodríguez and Carlos A. Coello Coello
Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement Learning
Jordan T. Bishop and Marcus Gallagher
Adaptive Stochastic Natural Gradient Method for Optimizing Functions with Low Effective Dimensionality
Teppei Yamaguchi, Kento Uchida, and Shinichi Shirakawa
Multi-Objective Magnitude-Based Pruning for Latency-Aware Deep Neural Network Compression
Wenjing Hong, Peng Yang, Yiwen Wang, and Ke Tang
Fitness Landscape Features and Reward Shaping in Reinforcement Learning Policy Spaces
Nathaniel du Preez-Wilkinson and Marcus Gallagher
Automatic Configuration of a Multi-Objective Local Search for Imbalanced Classification
Sara Tari, Holger Hoos, Julie Jacques, Marie-Elėonore Kessaci and Laetitia Jourdan
Improving Many-Objective Evolutionary Algorithms by Means of Edge-Rotated Cones
Yali Wang, André Deutz, Thomas Bäck and Michael Emmerich
On Stochastic Fitness Landscapes: Local Optimality and Fitness Landscape Analysis for Stochastic Search Operators
Brahim Aboutaib, Sébastien Verel, Cyril Fonlupt, Bilel Derbel, Arnaud Leifooghe and Belaïd Ahiod
Nash Equilibrium as Solution in Supervised Classification
Mihai-Alexandru Suciu and Rodica Ioana Lung
A Hybrid Evolutionary Algorithm for Reliable Facility Location Problem
Han Zhang, Jialin Liu, and Xin Yao
A Surrogate-assisted Evolutionary Algorithm with Random Feature Selection for Large-scale Expensive Problems
Guoxia Fu, Chaoli Sun, Ying Tan, Guochen Zhang, and Yaochu Jin
Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions
Jakob Bossek, Aneta Neumann, and Frank Neumann
Approximate Hypervolume calculation with guaranteed or confidence bounds
Andrzej Jaszkiewicz, Robert Susmaga, and Piotr Zielniewicz
Human Derived Heuristic Enhancement of an Evolutionary Algorithm for the 2D Bin Packing Problem
Nicholas Ross, Edward Keedwell, and Dragan Savic
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem
Moritz V. Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, and Heike Trautmann
On the Design of a Partition Crossover for the Quadratic Assignment Problem
Omar Abdelkafi, Bilel Derbel, Arnaud Liefooghe, and Darrell Whitley
Warm-Start AlphaZero Self-Play Search Enhancements
Hui Wang, Mike Preuss, and Aske Plaat
Proposal of a Realistic Many-Objective Test Suite
Weiyu Chen, Hisao Ishibuchi, and Ke Shang
Improving Sampling in Evolution Strategies through Mixture-based Distributions built from Past Problem Instances
Stephen Friess, Peter Tiňo, Stefan Menzel, Bernhard Sendhoff, and Xin Yao
A Committee of Convolutional Neural Networks for Image Classification in the Concurrent Presence of Feature and Label Noise
Stanisław Kaźmierczak and Jacek Mańdziuk
A New Paradigm in Interactive Evolutionary Multiobjective Optimization
Bhupinder Singh Saini, Jussi Hakanen, and Kaisa Miettinen
High Dimensional Bayesian Optimization assisted by Principal Component Analysis
Elena Raponi, Hao Wang, Mariusz Bujny, Simonetta Boria, and Carola Doerr
Evaluation of a Permutation-Based Evolutionary Framework for Lyndon Factorizations
Lily Major, Amanda Clare, Jacqueline W. Daykin, Benjamin Mora, Leonel Jose Peña Gamboa, and Christine Zarges
Fitness landscape analysis of dimensionally-aware genetic programming featuring Feynman equations
Marko Durasevic, Domagoj Jakobovic, Marcella Martins, Stjepan Picek, and Markus Wagner
Biologically Plausible Learning of Text Representation with Spiking Neural Networks
Marcin Białas, Marcin Michał Mirończuk, and Jacek Mańdziuk
Cooperative Co-Evolutionary GP for High Dimensional Problems
Lino Rodriguez-Coayahuitl, Alicia Morales-Reyes, Hugo J. Escalante, and Carlos A. Coello Coello
Learning a Formula of Interpretability to Learn Interpretable Formulas
Marco Virgolin, Andrea De Lorenzo, Eric Medvet, and Francesca Randone
Runtime Analysis of a Heavy-Tailed (1 + ( λ, λ )) Genetic Algorithm on Jump Functions
Denis Antipov and Benjamin Doerr
ClipUp: A Simple and Powerful Optimizer for Distribution-based Policy Evolution
Nihat Engin Toklu, Paweł Liskowski, and Rupesh Kumar Srivastava
First Steps Towards a Runtime Analysis When Starting With a Good Solution
Denis Antipov, Maxim Buzdalov, and Benjamin Doerr
Generic Relative Relations in Hierarchical Gene Expression Data Classification
Marcin Czajkowski, Krzysztof Jurczuk, and Marek Kretowski
Program Synthesis in a Continuous Space using Grammars and Variational Autoencoders
David Lynch, James McDermott, and Michael O’Neill
Generation of New Scalarizing Functions Using Genetic Programming
Amín V. Bernabé Rodríguez and Carlos A. Coello Coello
Analyzing the Components of Distributed Coevolutionary GANs Training
Jamal Toutouh, Erik Hemberg, and Una-May O’reilly
Neuromemetic Evolutionary Optimization
Paweł Liskowski, Krzysztof Krawiec, and Nihat Engin Toklu
Approximation Speed-up by Quadratization on LeadingOnes
Andrew M. Sutton and Darrell Whitley
Filter Sort is Ω( N3 ) in the Worst Case
Sumit Mishra and Maxim Buzdalov
Benchmarking a (μ + λ) Genetic Algorithm with Configurable Crossover Probability
Furong Ye, Hao Wang, Carola Doerr, and Thomas Bäck
Revisiting Population Models in Differential Evolution on a Limited Budget of Evaluations
Ryoji Tanabe
Evolutionary Graph-based V+E Optimization for Protection Against Epidemics
Krzysztof Michalak
Optimal Mutation Rates for the (1+λ) EA on OneMax
Maxim Buzdalov and Carola Doerr
A Search for Additional Structure: The Case of Cryptographic S-boxes
Claude Carlet, Marko Djurasevic, Domagoj Jakobovic, and Stjepan Picek
Parameter-less Population Pyramid for Permutation-based Problems
Szymon Wozniak, Michal Przewozniczek, and Marcin Komarnicki