Program
Monday, September 16:
Oliver Schütze received a PhD in
Mathematics from the University of Paderborn, Germany, in
2004. He is currently professor at the Cinvestav-IPN in Mexico City, Mexico. His
research interests
focus on numerical and evolutionary optimization with an emphasis on multi-objective
optimization
problems. He has co-authored more than 170 publications including 2 monographic
books, 5 text books
and 17 edited books. Google Scholar reports more than 4,500 citations and a Hirsch
index of 35.
During his career he received several prices and awards. For instance, he is
co-author of two papers
that won the IEEE CIS Outstanding Paper Award (for the IEEE TEC papers of 2010 and
2012), and is
recipient of the H. S. Hsu Award 2022. He is Editor-in-Chief of the journal
Mathematical and
Computational Applications, and member of the Editorial Board for Applied Soft
Computing,
Computational Optimization and Applications, Engineering Optimization, Results in
Control and
Optimization, and IEEE Transactions on Evolutionary Computation. He is founder of
the workshop
series Numerical and Evolutionary Optimization (NEO). Dr. Schuetze is member of the
Mexican Academy
of Sciences (AMC) and the National Network of Researchers (SNI Level III).
For more information about Oliver Schütze go to https://neo.cinvestav.mx/Group/.
Get the keynote slides here!
Tuesday, September 17:
Richard Kueng (Johannes Kepler
University Linz, AT) is full professor for Computing
Technologies. He pursues an interdisciplinary research agenda at the interface
between computer
science (algorithms & computational complexity), physics (quantum information &
quantum
technologies) and applied math (convex geometry & high dimensional probability
theory). Broadly
speaking, he aspires to develop efficient and simple solutions for important
algorithmic challenges
that also come with rigorous performance guarantees. Concrete examples are efficient
subroutines for
quantum and classical data processing, as well as (convex) optimization.
Applications in optics,
wireless communication, the math of voting and electronic design automation are also
within his
portfolio. Together with Hsin-Yuan Huang and John Preskill (both at Caltech),
Richard Kueng
developed the classical shadow formalism – an efficient quantum-to-classical
conversion procedure
that has made a lasting impact on quantum computing technologies.
In 2023, Richard Kueng received both an FWF START Award and an ERC Starting Grant.
As of 2024, he's
also an elected member of the young wing of the Austrian Academy of Sciences.
For more information about Richard Kueng go to https://iic.jku.at/team/kueng/.
Get the keynote slides here!
Wednesday, September 18:
Bernardino Romera-Paredes (Google
DeepMind) is a former core team member of AlphaFold2 and
AlphaTensor and now research scientist at Google DeepMind in London. At PPSN 2024
Bernardino
Romera-Paredes will present his current research regarding the evolution of new
heuristics,
supported by pairing a pre-trained LLM and an automated "evaluator", with his
keynote "FunSearch:
Discovering new mathematics and algorithms using Large Language Models". In this
talk I will present
FunSearch, a method to search for new solutions in mathematics and computer science.
FunSearch works
by pairing a pre-trained LLM, whose goal is to provide creative solutions in the
form of computer
code, with an automated “evaluator”, which guards against hallucinations and
incorrect ideas. By
leveraging these two components within an evolutionary algorithm, initial solutions
“evolve” into
new knowledge. I will present the application of FunSearch to a central problem in
extremal
combinatorics — the cap set problem — where we discover new constructions of large
cap sets going
beyond the best known ones, both in finite dimensional and asymptotic cases. This
represents the
first discoveries made for established open problems using LLMs. Then, I will
present the
application of FunSearch to an algorithmic problem, online bin packing, which
showcases the
generality of the method. In this use case, FunSearch finds new heuristics that
improve upon widely
used baselines. I will conclude the talk by discussing the implications of searching
in the space of
code.
For more information about Bernardino Romera-Paredes go to https://www.romera-paredes.com/.
Get the keynote slides here!
| Names | Title | Resources |
|---|---|---|
| Benjamin Doerr, Concha Bielza, John McCall, and Weijie Zheng | 30 Years of EDAs (more information at https://30yearsofedas.github.io) | |
| Tinkle Chugh, George De Ath, Paul Kent, Alma Rahat, Kaifeng Yang | BOSS: Bayesian and Surrogate-assisted Search and Optimisation | |
| Heike Trautmann, Lennart Schapermeier, Oliver Schuetze | Multimodal Multi-objective Optimization | Slides |
| Carola Doerr, Vanessa Volz, Boris Naujoks, Olaf Mersmann, Mike Preuss, Pascal Kerschk | Good Benchmarking Practices for Evolutionary Computation BENCHMARKING@PPSN2024 |
| Names | Title | Resources |
|---|---|---|
| Nelishia Pillay | Transfer Learning in Evolutionary Spaces | |
| Ofer M. Shir | Mathematical Programming as a Complement to Bio-Inspired Optimization | Slides |
| Kate Smith-Miles and Mario Andrés Muñoz Acosta | Instance Space Analysis for Rigorous and Insightful Algorithm Testing | |
| Chao Qian | Pareto Optimization for Subset Selection: Theories and Practical Algorithms | Slides |
| Benjamin Doerr | A Gentle Introduction to Theory (for Non-Theoreticians) | Slides |
| Michal Pluhacek, Adam Viktorin, Roman Senkerik | Large Language Models as Tools for Metaheuristic Design: Exploring Challenges and Opportunities | |
| A.E. Eiben | Robot Evolution | |
| Ke Li | Decomposition Evolutionary Multi-Objective Optimization: What We Know from the Literature and What We are not Clear from a Data Science Perspective | |
| Michael Hellwig, Steffen Finck, and Hans-Georg Beyer | Introduction to Evolution Strategies for Constrained Optimization Problems | |
| Martin Krejca | Theory of Estimation-of-Distribution Algorithms | Slides |
| Jeroen Rook, Manuel López-Ibáñez, and Heike Trautmann | Advanced Use of Automatic Algorithm Configuration: Single- and Multi-Objective Approaches | Slides |
| Bogdan Filipič, Aljosa Vodopija | Constraint Handling in Multiobjective Optimization | Slides |
| Nikolaus Hansen | CMA-ES | |
| Per Kristian Lehre | Runtime Analysis of Population-based Evolutionary Algorithms | |
| Per Kristian Lehre, Mario A. Hevia Fajardo | Adversarial Optimisation through Competitive Co-evolutionary Algorithms | |
| Anna V. Kononova, Niki van Stein, Diederick Vermetten | Structural bias in optimisation algorithms |
| Authors | Title | Category | Session |
|---|---|---|---|
| Gijs Schröder, Inge Wortel, Johannes Textor | Population-Based Algorithms Built on Weighted Automata | (Evolutionary) Machine Learning and Neuroevolution | Poster Session 1 |
| Fuda van Diggelen, Matteo de Carlo, Nicolas Cambier, Eliseo Ferrante, A.E. Eiben | Emergence of Specialised Collective Behaviors in Evolving Heterogeneous Swarms | Automated Algorithm Selection and Configuration | Poster Session 1 |
| Rui Zhang, Fei Liu, Xi Lin, Zhenkun Wang, Zhichao Lu, Qingfu Zhang | Understanding the Importance of Evolutionary Search in Automated Heuristic Design with Large Language Models | Automated Algorithm Selection and Configuration | Poster Session 1 |
| Ali Ahrari, Ruhul Sarker, Carlos Coello Coello | Aggregated Partial Hypervolumes - An Overall Indicator for Performance Evaluation of Multimodal Multiobjective Optimization Methods | Benchmarking and Performance Measures | Poster Session 1 |
| Petrica Pop Sitar, Cosmin Sabo, Adrian Petrovan, Adrian Petrovan | On the design of diploid memetic algorithms for solving the multidimensional multi-way number partitioning problem | Combinatorial Optimization | Poster Session 1 |
| Han Zhang, Qing Li, Xin Yao | Knowledge-Guided Optimization for Complex Vehicle Routing with 3D Loading Constraints | Combinatorial Optimization | Poster Session 1 |
| Christopher Crary, Bogdan Burlacu, Wolfgang Banzhaf | Enhancing the Computational Efficiency of Genetic Programming through Alternative Floating-Point Primitives | Genetic Programming | Poster Session 1 |
| Kai Li, Kangnian Lin, Ruihao Zheng, Zhenkun Wang | Selection Strategy Based on Proper Pareto Optimality in Evolutionary Multi-Objective Optimization | Multi-Objective Optimization | Poster Session 1 |
| Kenneth Zhang, Ke Shang, Oliver Schuetze, Angel Rodriguez-Fernandez | Hypervolume gradient subspace approximation | Multi-Objective Optimization | Poster Session 1 |
| Cheng Gong, Ping Guo, Hisao Ishibuchi, Qingfu Zhang, Tianye Shu | LTR-HSS: A Learning-to-Rank based Framework for Hypervolume Subset Selection | Multi-Objective Optimization | Poster Session 1 |
| Claude Carlet, Marko Đurasević, Domagoj Jakobovic, Stjepan Picek | Discovering Rotation Symmetric Self-dual Bent Functions with Evolutionary Algorithms | Real-World Applications | Poster Session 1 |
| Konstantin Sturm, Johannes Lengler | Self-Adjusting Evolutionary Algorithms Are Slow on a Class of Multimodal Landscapes | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 1 |
| Frank Neumann, Carsten Witt | Sliding Window 3-Objective Pareto Optimization for Problems with Chance Constraints | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 1 |
| Rafał Dreżewski, Shoffan Saifullah | Automatic Brain Tumor Segmentation Using Convolutional Neural Networks: U-Net Framework with PSO-Tuned Hyperparameters | (Evolutionary) Machine Learning and Neuroevolution | Poster Session 2 |
| Quentin Renau, Emma Hart | Identifying Easy Instances to Improve Efficiency of ML Pipelines for Algorithm-Selection | Automated Algorithm Selection and Configuration | Poster Session 2 |
| Diederick Vermetten, Johannes Lengler, Dimitri Rusin, Thomas Baeck, Carola Doerr | Empirical Analysis of the Dynamic Binary Value Problem with IOHprofiler | Benchmarking and Performance Measures | Poster Session 2 |
| Xiankun Yan, Aneta Neumann, Frank Neumann | Sliding Window Bi-Objective Evolutionary Algorithms for Optimizing Chance-Constrained Monotone Submodular Functions | Combinatorial Optimization | Poster Session 2 |
| Babak Hosseinkhani Kargar, Karine Miras, A.E. Eiben | Exploring proprioceptive feedback in the evolution of modular robots | Evolvable Hardware and Evolutionary Robotics | Poster Session 2 |
| Miguel Rabuge, Nuno Lourenço | Decision Tree Based Wrappers for Hearing Loss | Genetic Programming | Poster Session 2 |
| Camilo De La Torre, Yuri Lavinas, Kevin Cortacero, Dennis Wilson, Sylvain Cussat-Blanc | Multi-Modal Adaptive Graph Evolution for Program Synthesis | Genetic Programming | Poster Session 2 |
| Cheng Gong, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang | Three objectives degrade the convergence ability of dominance-based multi-objective evolutionary algorithms | Multi-Objective Optimization | Poster Session 2 |
| Yilu LIU, Chengyu LU, Xi LIN, Qingfu ZHANG | Many-Objective Cover Problem: Discovering Few Solutions to Cover Many Objectives | Multi-Objective Optimization | Poster Session 2 |
| Clément Legrand, Diego Cattaruzza, Laetitia JOURDAN, Marie-Eléonore Kessaci | Solution-based Knowledge Discovery for Multi-objective Optimization | Multi-Objective Optimization | Poster Session 2 |
| Romain Michelucci, Denis Pallez, Tristan Cazenave, Jean-Paul Comet | Improving continuous Monte Carlo Tree Search for identifying parameters in hybrid Gene Regulatory Networks | Real-World Applications | Poster Session 2 |
| Antipov Denis, Aneta Neumann, Frank Neumann, Andrew Sutton | Runtime Analysis of Evolutionary Diversity Optimization on a Tri-Objective Version of the (LeadingOnes, TrailingZeros) Problem | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 2 |
| Sumit Adak, Carsten Witt | Runtime Analysis of a Multi-Valued Compact Genetic Algorithm on Generalized OneMax | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 2 |
| Damy Ha, Tanja Alderliesten, Peter Bosman | Learning Discretized Bayesian Networks with GOMEA | (Evolutionary) Machine Learning and Neuroevolution | Poster Session 3 |
| Fu Xing Long, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Baeck, Niki van Stein | Landscape-aware Automated Algorithm Configuration using Multi-output Mixed Regression and Classification | Automated Algorithm Selection and Configuration | Poster Session 3 |
| Kei Nishihara, Masaya Nakata | A Surrogate-assisted Partial Optimization for Expensive Constrained Optimization Problems | Bayesian- and Surrogate-Assisted Optimization | Poster Session 3 |
| Niki van Stein, Sarah L. Thomson, Anna V. Kononova | A Deep Dive into Effects of Structural Bias on CMA-ES Performance along Affine Trajectories | Benchmarking and Performance Measures | Poster Session 3 |
| SAINING LIU, Joao Guilherme Cavalcanti Costa, Yi Mei, Mengjie Zhang | GPGLS: Genetic Programming Guided Local Search for Large-Scale Vehicle Routing Problems | Combinatorial Optimization | Poster Session 3 |
| Gabriela Ochoa, Sébastien Verel, Arnaud Liefooghe | Funnels in Multi-objective Fitness Landscapes | Fitness Landscape Modeling and Analysis | Poster Session 3 |
| Marko Đurasević, Mateja Đumić, Francisco Javier Gil-Gala, Nikolina Frid, Domagoj Jakobović | Improving the performance of relocation rules for the container relocation problem with the rollout algorithm | Genetic Programming | Poster Session 3 |
| Eva Röper, Jens Weise, Christoph Steup, Sanaz Mostaghim | Innovization for Route Planning | Multi-Objective Optimization | Poster Session 3 |
| Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann | Evolutionary Multi-Objective Diversity Optimization | Multi-Objective Optimization | Poster Session 3 |
| Tingyang Wei, Abhishek Gupta, Yew-Soon Ong, Puay Siew Tan, Jiao Liu | Bayesian Forward-Inverse Transfer for Multiobjective Optimization | Multi-Objective Optimization | Poster Session 3 |
| Darrell Whitey, Ozeas Quevedo De Carvalho, Mark Roberts, Vivant Shetty, Piyabutra Jampathom | Satellite Resource Scheduling: Compaction Strategies for Genetic Algorithm Schedulers | Real-World Applications | Poster Session 3 |
| Ulysse Schaller, Marc Kaufmann, Johannes Lengler, Cella Florescu | Faster Optimization Through Genetic Drift | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 3 |
| Antipov Denis, Timo Kötzing, Aishwarya Radhakrishnan | Greedy versus Curious Parent Selection for Multi-Objective Evolutionary Algorithms | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 3 |
| Ganyuan Luo, Hao Li, Yuren Zhou, Zefeng Chen | Pareto-Informed Multi-Objective Neural Architecture Search | (Evolutionary) Machine Learning and Neuroevolution | Poster Session 4 |
| Darian Reyes Fernández de Bulnes, Allan de Lima, Edgar Galván, Conor Ryan | Feature Encapsulation by Stages in the Regression Domain Using Grammatical Evolution | Automated Algorithm Selection and Configuration | Poster Session 4 |
| Yiming Yao, Fei Liu, Ji Cheng, Qingfu Zhang | Evolve Cost-aware Acquisition Functions Using Large Language Models | Bayesian- and Surrogate-Assisted Optimization | Poster Session 4 |
| Francisco Chicano, Darrell Whitey, Gabriela Ochoa, Renato Tinos | Generalizing and Unifying Gray-box Combinatorial Optimization Operators | Combinatorial Optimization | Poster Session 4 |
| Arnaud Liefooghe, Ryoji Tanabe, Sébastien Verel | Contrasting the Landscapes of Feature Selection under Different Machine Learning Models | Fitness Landscape Modeling and Analysis | Poster Session 4 |
| Gabriel Kronberger, Fabricio Olivetti de Franca, Harry Desmond, Deaglan Bartlett, Lukas Kammerer | The Inefficiency of Genetic Programming for Symbolic Regression | Genetic Programming | Poster Session 4 |
| Simon Wietheger, Benjamin Doerr | Near-Tight Runtime Guarantees for Many-Objective Evolutionary Algorithms | Multi-Objective Optimization | Poster Session 4 |
| Felipe Honjo Ide, Hernan Aguirre, Kiyoshi Tanaka | Multi-Objective Random Bit Climbers with Weighted Permutation on Large Scale Binary MNK-Landscapes | Multi-Objective Optimization | Poster Session 4 |
| Jacob de Nobel, Diederick Vermetten, Anna Kononova, Ofer Shir, Thomas Baeck | Avoiding Redundant Restarts in Multimodal Global Optimization | Numerical Optimization | Poster Session 4 |
| Ritam Guha, Ryan Mckendrick, Bradley Feest, Kalyanmoy Deb | Attacker-Defender Strategy Optimization Using Multi-objective Competitive Co-evolution | Real-World Applications | Poster Session 4 |
| Sacha Cerf, Johannes Lengler | How Population Diversity Influences the Efficiency of Crossover | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 4 |
| Per Kristian Lehre, Shishen Lin | Overcoming Binary Adversarial Optimisation with Competitive Coevolution | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 4 |
| Hiroki Shiraishi, Rongguang Ye, Hisao Ishibuchi, Masaya Nakata | A Variable-Length Fuzzy Set Representation for Learning Fuzzy-Classifier Systems | (Evolutionary) Machine Learning and Neuroevolution | Poster Session 5 |
| Emma Hart, Quentin Renau, Kevin Sim, Mohamad Alissa | Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances | Automated Algorithm Selection and Configuration | Poster Session 5 |
| Quanlin Chen, Jing Huo, Yiyu Chen, Tianyu Ding, Yang Gao | Re-Examining Supervised Dimension Reduction for High-Dimensional Bayesian Optimization | Bayesian- and Surrogate-Assisted Optimization | Poster Session 5 |
| MARIA N. ANASTASIADOU, Michalis Mavrovouniotis, Diofantos Hadjimitsis | Ant Colony Optimization for the Dynamic Electric Vehicle Routing Problem | Combinatorial Optimization | Poster Session 5 |
| Sarah L. Thomson, Gabriela Ochoa, Daan van den Berg, Tianyu Liang, Thomas Weise | Entropy, Search Trajectories, and Explainability for Frequency Fitness Assignment | Fitness Landscape Modeling and Analysis | Poster Session 5 |
| Yuri Lavinas, Nathaniel Haut, William Punch, Wolfgang Banzhaf, Sylvain Cussat-Blanc | Adaptive Sampling of Biomedical Images with Cartesian Genetic Programming | Genetic Programming | Poster Session 5 |
| Rongguang Ye, Longcan Chen, Jinyuan Zhang, Hisao Ishibuchi | An Unbounded Archive-Based Inverse Model in Evolutionary Multi-objective Optimization | Multi-Objective Optimization | Poster Session 5 |
| Lennart Schäpermeier, Pascal Kerschke | Reinvestigating the R2 Indicator: Achieving Pareto Compliance by Integration | Multi-Objective Optimization | Poster Session 5 |
| Ryoki Hamano, Shinichi Shirakawa, Masahiro Nomura | Natural Gradient Interpretation of Rank-One Update in CMA-ES | Numerical Optimization | Poster Session 5 |
| Lee A. Christie, Atakan Sahin, Akinola Ogunsemi, John A. W. McCall, Alexandru-Ciprian Zavoianu | On the Multi-Objective Optimization of Wind Farm Cable Layouts with regard to Cost and Robustness | Real-World Applications | Poster Session 5 |
| Andrew Sutton, Jiwon Lee | Evolving Populations of Solved Subgraphs with Crossover and Constraint Repair | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 5 |
| Jonathan Gadea Harder, Aneta Neumann, Frank Neumann | Analysis of Evolutionary Diversity Optimisation for the Maximum Matching Problem | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 5 |
| Frank Neumann, Guenter Rudolph | Archive-based Single-Objective Evolutionary Algorithms for Submodular Optimization | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 5 |
| Moritz Seiler, Urban Skvorc, Gjorgjina Cenikj, Carola Doerr, Heike Trautmann | Learned Features vs. Classical ELA on Affine BBOB Functions | Automated Algorithm Selection and Configuration | Poster Session 6 |
| Stefan Pricopie, Richard Allmendinger, Manuel López-Ibáñez, Clyde Fare, Matt Benatan, Joshua Knowles | An adaptive approach to Bayesian Optimization with switching costs | Bayesian- and Surrogate-Assisted Optimization | Poster Session 6 |
| Tristan Cazenave | Learning a Prior for Monte Carlo Search by Replaying Solutions to Combinatorial Problems | Combinatorial Optimization | Poster Session 6 |
| Darrell Whitey, Gabriela Ochoa, Francisco Chicano | Over Sampling Local Optima: Selection and Sampling Bias in Hybrid Genetic Algorithms | Fitness Landscape Modeling and Analysis | Poster Session 6 |
| jinglu song, Qiang Lu, bozhou tian, jingwen zhang, jake luo, zhiguang wang | Symbol Graph Genetic Programming for Symbolic Regression | Genetic Programming | Poster Session 6 |
| Johannes Koch, Tanja Alderliesten, Peter Bosman | Simultaneous Model-Based Evolution of Constants and Expression Structure in GP-GOMEA for Symbolic Regression | Genetic Programming | Poster Session 6 |
| Dan-Xuan Liu, Chao Qian | Biased Pareto Optimization for Subset Selection with Dynamic Cost Constraints | Multi-Objective Optimization | Poster Session 6 |
| Rodolfo Humberto Tamayo, Jesús Guillermo Falcón-Cardona, Carlos A. Coello Coello | Reaching Pareto Front Shape Invariance with a Continuous Multi-Objective Ant Colony Optimization Algorithm | Multi-Objective Optimization | Poster Session 6 |
| Kento Uchida, Ryoki Hamano, Masahiro Nomura, Shota Saito, Shinichi Shirakawa | CMA-ES for Discrete and Mixed-Variable Optimization on Sets of Points | Numerical Optimization | Poster Session 6 |
| Egor Bazhenov, Ivan Jarsky, Sergey Muravyov, Valeria Efimova | EvoVec: Evolutionary Image Vectorization with Adaptive Curve Number and Color Gradients | Real-World Applications | Poster Session 6 |
| Antipov Denis, Aneta Neumann, Frank Neumann | Local Optima in Diversity Optimization: Non-trivial Offspring Population is Essential | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 6 |
| Benjamin Doerr, Martin Krejca, Noé Weeks | Proven Runtime Guarantees for How the MOEA/D Computes the Pareto Front From the Subproblem Solutions | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 6 |
| Mingfeng Li, Weijie Zheng, Xie Wen, sun ao, Xin Yao | When Does the Time-Linkage Property Help Optimization by Evolutionary Algorithms? | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 6 |
| Konstantin Dietrich, Raphael Patrick Prager, Carola Doerr, Heike Trautmann | Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization | Automated Algorithm Selection and Configuration | Poster Session 7 |
| Cedric Rodriguez, Peter Bosman, Tanja Alderliesten | Balancing Between Time Budgets and Costs in Surrogate-Assisted Evolutionary Algorithms | Bayesian- and Surrogate-Assisted Optimization | Poster Session 7 |
| Jonathan Heins, Lennart Schäpermeier, Pascal Kerschke, Darrell Whitey | Dancing to the State of the Art? How Candidate Lists Influence LKH for Solving the Traveling Salesperson Problem | Combinatorial Optimization | Poster Session 7 |
| Xavier F. C. Sánchez-Díaz, Corentin Masson, Ole Jakob Mengshoel | Regularized Feature Selection Landscapes: An Empirical Study of Multimodality | Fitness Landscape Modeling and Analysis | Poster Session 7 |
| Hengzhe Zhang, Qi Chen, Bing Xue, Mengjie Zhang, Wolfgang Banzhaf | P-Mixup: Improving Generalization Performance of Evolutionary Feature Construction with Pessimistic Vicinal Risk Minimization | Genetic Programming | Poster Session 7 |
| Stefano Genetti, Eros Ribaga, Quintino Francesco Lotito, Giovanni Iacca, Elia Cunegatti | Influence Maximization in Hypergraphs using Multi-Objective Evolutionary Algorithms | Multi-Objective Optimization | Poster Session 7 |
| Zakaria A. DAHI, Francisco Chicano, Gabriel Luque, Enrique Alba, Bilel Derbel | Scalable Quantum Approximate Optimiser for Pseudo-Boolean Multi-Objective Optimisation | Multi-Objective Optimization | Poster Session 7 |
| Stephan Frank, Tobias Glasmachers | A Potential Potential Function for a Variable-Metric Evolution Strategy | Numerical Optimization | Poster Session 7 |
| Runlong Yu, Robert Ladwig, Xiang Xu, Peijun Zhu, Paul Hanson, Yiqun Xie, Xiaowei Jia | Evolution-based Feature Selection for Predicting Dissolved Oxygen Concentrations in Lakes | Real-World Applications | Poster Session 7 |
| Mario Alejandro Hevia Fajardo, Per Kristian Lehre | Ranking Diversity Benefits Coevolutionary Algorithms on an Intransitive Game | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 7 |
| Duc-Cuong Dang, Andre Opris, Dirk Sudholt | On the Equivalence between Stochastic Tournament and Power-law Ranking Selection and How to Implement them Efficiently | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 7 |
| Renzhong Deng, Weijie Zheng, Mingfeng Li, Jie Liu, Benjamin Doerr | Runtime Analysis for State-of-the-Art Multi-Objective Evolutionary Algorithms on the Subset Selection Problem | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 7 |
| Konrad Gmyrek, Pawel Myszkowski, Michał Antkiewicz, Łukasz Olech | iMOPSE: a Comprehensive Open Source Library for single- and multi-objective Metaheuristic Optimization | Automated Algorithm Selection and Configuration | Poster Session 8 |
| Jakub Kudela, Ladislav Dobrovsky | Performance Comparison of Surrogate-Assisted Evolutionary Algorithms on Computational Fluid Dynamics Problems | Bayesian- and Surrogate-Assisted Optimization | Poster Session 8 |
| Kokila Perera, Frank Neumann, Aneta Neumann | Multi-Objective Evolutionary Approaches for the Knapsack Problem with Stochastic Profits | Combinatorial Optimization | Poster Session 8 |
| Henning Cui, Michael Heider, Jörg Hähner | Positional Bias Does Not Influence Cartesian Genetic Programming with Crossover | Genetic Programming | Poster Session 8 |
| Julia Reuter, Viktor Martinek, Roland Herzog, Sanaz Mostaghim | Unit-Aware Genetic Programming for the Development of Empirical Equations | Genetic Programming | Poster Session 8 |
| Lie Meng Pang, Hisao Ishibuchi, Yang Nan, Cheng Gong | Reliability of Indicator-based Comparison Results of Evolutionary Multi-Objective Algorithms | Multi-Objective Optimization | Poster Session 8 |
| Zimin Liang, Zhiji Cui, Miqing Li | Pareto Landscape: Visualising the Landscape of Multi-Objective Optimisation Problems | Multi-Objective Optimization | Poster Session 8 |
| Yuta Sekino, Kento Uchida, Shinichi Shirakawa | Warm Starting of CMA-ES for Contextual Optimization Problems | Numerical Optimization | Poster Session 8 |
| Tristan Marty, Nikolaus Hansen, Anne Auger, Yann Semet, Sébastien Héron | LB+IC-CMA-ES: Two simple modifications of CMA-ES to handle mixed-integer problems | Other | Poster Session 8 |
| Sara Mandujano, Adriana Lara López, Juan Carlos Ku Cauich | Using Evolutionary Algorithms for the search of 16-variable Weight-Wise Perfectly Balanced Boolean Functions with high Non-Linearity | Real-World Applications | Poster Session 8 |
| Duc-Cuong Dang, Andre Opris, Dirk Sudholt | Level-based Theorems for Runtime Analysis of Multi-objective Evolutionary Algorithms | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 8 |
| Shengjie Ren, Chao Qian, Chao Bian, Miqing Li | A First Running Time Analysis of the Strength Pareto Evolutionary Algorithm 2 (SPEA2) | Theoretical Aspects of Nature-Inspired Optimization | Poster Session 8 |