- 160 contributions have been accepted as posters. They will be published in the Companion Volume (and hence in the Digital Library) and shown during the poster session of the conference.
- Search the list below by typing text in the column headers.
- See also the list of accepted papers.
- The Call for Papers and the Papers Submission Instructions are still available for your information.
List of Accepted Posters
| Track | Title | Authors |
|---|---|---|
| L4EC | Evolution Transformer: In-Context Evolutionary Optimization | Robert Lange (Technical Univ. Berlin, Google DeepMind), Yingtao Tian (Google DeepMind), Yujin Tang (Google DeepMind) |
| ECOM | A Secure Simulation-optimisation Framework for Fleet Mix Problem: A Defence-based Real-world Application | Sara Elsayed Salim (University of New South Wales), Ismail Mohamed Ali (University of New South Wales), Sondoss Elsawah (University of New South Wales) |
| EML | Evolutionary Data Subset Selection for Class-Incremental Learning on Memory-Constrained Systems | Epifanios Baikas (University of Southampton), Danesh Tarapore (University of Southampton), David Thomas (University of Southampton) |
| RWA | Selecting Image Features for Biopsy Needle Detection in Ultrasound Images Using Genetic Algorithms | Agata M. Wijata (Silesian University of Technology), Bartłomiej Pyciński (Silesian University of Technology), Jakub Nalepa (Silesian University of Technology) |
| GECH | Morpho-Material Evolution for Automated Robot Design | Geoff Nitschke (University of Cape Town), Bilal Aslan (University of Cape Town) |
| EML | Multi-Criterion Feature Selection Based on Clustering Symbolic Regression | Yehang Chen (University of Electronic Science and Technology of China), Yu Zhang (University of Electronic Science and Technology of China), Xinyue Li (University of Electronic Science and Technology of China), Wang Hu (University of Electronic Science and Technology of China) |
| ECOM | Enhancing Electric Vehicle Charging Schedules: A Surrogate-Assisted Approach | Abdennour Azerine (Université de Haute-Alsace), Mahmoud Golabi (Université de Haute-Alsace), Ammar Oulamara (Université de Lorraine), Lhassane Idoumghar (Université de Haute-Alsace) |
| EMO | Composite Quality Indicators to Evaluate the Performance of Population-based Multiobjective Optimization Algorithms | Rubén Saborido (University of Malaga), Ana Belén Ruiz (University of Malaga), Sandra Gonzalez-Gallardo (University of Malaga), Mariano Luque (University of Malaga), Antonio Borrego (University of Malaga) |
| EMO | A Multi-objective Evolutionary Algorithm based on Hierarchical Grouping for Large-scale Multi-objective Optimization | Qingwei Liang (Shandong University of Science and Technology), Shu-Chuan Chu (Shandong University of Science and Technology), Pei-Cheng Song (Shandong University of Science and Technology), Jia Zhao (Nanchang Institute of Technology), Zne-jung Lee (Fuzhou University), Jeng-Shyang Pan (Shandong University of Science and Technology, Chaoyang University of Technology) |
| L4EC | Large Language Models As Evolution Strategies | Robert Lange (Technical Univ. Berlin, Google DeepMind), Yingtao Tian (Google DeepMind), Yujin Tang (Google DeepMind) |
| GA | An Empirical Study of Constrained Evolutionary Algorithms for Isomorphic Connected Graph Segmentation Problems | Feng Zhuang (Guangzhou Institute of Technology, Xidian University), Ting Huang (Guangzhou Institute of Technology, Xidian University), He Yu (Guangzhou Institute of Technology, Xidian University), Jing Liu (Guangzhou Institute of Technology, Xidian University) |
| RWA | On the Evolution of Boolean Functions with the Algebraic Normal Form Representation | Claude Carlet (University of Bergen), Marko Durasevic (University of Zagreb), Domagoj Jakobovic (University of Zagreb), Stjepan Picek (Radboud University) |
| SI | Orthogonally Initiated Particle Swarm Optimization with Advanced Mutation for Real-Parameter Optimization | Indu Bala (The University of Adelaide), Dikshit Chauhan (Dr. B.R. Ambedkar National Institute of Technology), Lewis Mitchell (The University of Adelaide) |
| RWA | An Optimised Light Gradient Boosting Machine Model for Setup Time Prediction in Electronic Production Lines | Siping Chen (The University of Newcastle), Debiao Li (Fuzhou University), Xiqin Gan (Fuzhou University), Raymond Chiong (The University of New England) |
| ENUM | Algorithm Performance Comparison for Integer-Valued OneMax | Xiaoyue Li (Hasso Plattner Institute, University of Potsdam), Timo Kötzing (Hasso Plattner Institute, University of Potsdam) |
| EML | Efficient Pruning of DenseNet via a Surrogate-Model-Assisted Genetic Algorithm | Jingeun Kim (Gachon University), Yourim Yoon (Gachon University) |
| ECOM | Adapted Ant Colony Optimization for Large-Scale Orienteering Problem | De Ming Wu (Zhejiang Normal University), Qiang Yang (Nanjing University of Information Science and Technology), Chang Jun Zhou (Zhejiang Normal University), Zhong Long Zheng (Zhejiang Normal University), Jun Zhang (Nankai University) |
| GA | Revisiting Evolutionary Algorithms for Optimization for Deep Learning: Introducing DL-HEA | Toki Tahmid Inan (George Mason University), Amarda Shehu (George Mason University) |
| EMO | How to Make Multi-Objective Evolutionary Algorithms Invariant to Monotonically Increasing Transformation of Objective Functions | Yutaro Yamada (Yokohama National University), Kento Uchida (Yokohama National University), Shinichi Shirakawa (Yokohama National University) |
| ECOM | Combining Adaptive Large Neighborhood Search with Guided Ejection Search for Real-World Multiple-Vehicle Pickup and Delivery Problem with Time Windows | Tri Phan (University of Information Technology (UIT), VNU-HCM, Vietnam National University - Ho Chi Minh City (VNU-HCM)), Khang Tran (University of Information Technology (UIT), VNU-HCM, Vietnam National University - Ho Chi Minh City (VNU-HCM)), Ngoc Hoang Luong (University of Information Technology (UIT), VNU-HCM, Vietnam National University - Ho Chi Minh City (VNU-HCM)) |
| CS | Solving Deceptive Problems Without Explicit Diversity Maintenance | Ryan Boldi (University of Massachusetts Amherst), Li Ding (University of Massachusetts Amherst), Lee Spector (Amherst College, University of Massachusetts Amherst) |
| GP | Runtime phylogenetic analysis enables extreme subsampling for test-based problems | Alexander Lalejini (Grand Valley State University), Marcos Sanson (Grand Valley State University), Jack Garbus (Brandeis University), Matthew Andres Moreno (University of Michigan), Emily Dolson (Michigan State University) |
| SI | Particle Swarm Optimization with Unfeasible Personal Best for Constrained Problems | So Fukuhara (Kagawa University), Masao Arakawa (Wasada University) |
| EMO | Interactive tool for visualizing the comprehensive performance of evolutionary multi-objective algorithms applied to problems with two or three objectives | Michał Tomczyk (Poznan University of Technology), Miłosz Kadziński (Poznan University of Technology) |
| RWA | Generating Solvable and Difficult Logic Grid Puzzles | Fiona Shyne (Northeastern University), Kaylah Facey (Northeastern University), Seth Cooper (Northeastern University) |
| RWA | Enhanced Surrogate-Assisted Multi-Objective Differential Evolution Algorithm with Self-Adaptive Strategies for Order Planning in Hot Rolling Process | Gelegen Che (National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education), Lixin Tang (National Frontiers Science Center for Industrial Intelligence and Systems Optimization), Guodong Zhao (Liaoning Key Laboratory of Manufacturing System and Logistics Optimization), Qingxin Guo (Liaoning Key Laboratory of Manufacturing System and Logistics Optimization), Jianqiang Guo (Liaoning Key Laboratory of Manufacturing System and Logistics Optimization) |
| EML | Immuno-inspired Selective Aggregation for Decentralized Federated Deep Reinforcement Learning | Gayathri Rangu (Indian Institute of Technology Guwahati), Shivashankar B. Nair (Indian Institute of Technology Guwahati) |
| EML | Generating High-Dimensional Prototypes with a Classifier System by Evolving in Latent Space | Naoya Yatsu (The University of Electro-Communications), Hiroki Shiraishi (Yokohama National University), Hiroyuki Sato (The University of Electro-Communications), Keiki Takadama (The University of Electro-Communications) |
| L4EC | Final Productive Fitness for Surrogates in Evolutionary Algorithms | Maximilian Zorn (LMU Munich), Sarah Gerner (LMU Munich), Philipp Altmann (LMU Munich), Thomas Gabor (LMU Munich) |
| ECOM | "A Cooperative Multi Indicator-Based Ant Colony Optimization Algorithm for the MOGenConVRP" | Rodrigo Fernando Velázquez Cruz (IIMAS-UNAM), Carlos Ignacio Hernández Castellanos (IIMAS-UNAM) |
| BBSR | Towards an Improved Understanding of Features for More Interpretable Landscape Analysis | Marcus R. Gallagher (University of Queensland), Mario Andres Munoz (The University of Melbourne) |
| EMO | Expensive Constrained Multi-objective Evolutionary Algorithm with Pareto Set Learning | Ruitao Mai (Shantou University), Yifeng Qiu (Shantou University), Wenji Li (Shantou University), Zhaojun Wang (Shantou University), Biao Xu (Shantou University), Wei Chen (Guangdong University of Technology), Jiafan Zhuang (Shantou University), Yun Li (Shenzhen Institute for Advanced Study, UESTC), Zhun Fan (University of Electronic Science and Technology of China) |
| RWA | Decomposition and Clustering-Based Many-Objective Optimizations for Multi-Label Feature Selection | Somayeh Kanani (University of Kurdistan), Parham Moradi (RMIT University, University of Kurdistan), Mahdi Jalili (RMIT University) |
| RWA | Dynamic Evaluation Functions Based Routing and Wavelength Assignment Optimization for Optical Network Capacity Expansion | Yu Fu (Huazhong University of Science and Technology) |
| GECH | Deficiencies of Best-chromosome-wins Dominance in Evolutionary Optimization of Stationary Functions | Maciej Komosinski (Poznan University of Technology), Marcin Leszczyński (Poznan University of Technology), Konrad Miazga (Poznan University of Technology), Dawid Siera (Poznan University of Technology) |
| EML | An Improved Evolutionary Reinforcement Learning Algorithm for UAV Online Target Tracking | Bai-Jiang Yu (South China University of Technology), Feng-Feng Wei (South China University of Technology), Tai-You Chen (South China University of Technology), Wei-Neng Chen (South China University of Technology) |
| EMO | Accelerated Bayesian Preference Learning for Efficient Evolutionary Multi-objective Optimisation | Kendall Taylor (RMIT University), Huong Ha (RMIT University), Minyi Li (Coles Group), Xiaodong Li (RMIT University) |
| GP | Archive-based multiple feature construction method using adaptive Genetic Programming | kaixuan Jia (College of Information Science and Technology, Hebei Agricultural University), Xiaoying Gao (Victoria University of Wellington), Jiaxin Niu (College of Information Science and Technology, Hebei Agricultural University), jianbin Ma (College of Information Science and Technology, Hebei Agricultural University) |
| CS | Generating Diverse Critics for Conditioned Policy Distillation | Ryan Boldi (University of Massachusetts Amherst), Matthew C. Fontaine (University of Southern California), Sumeet Batra (University of Southern California), Gaurav S. Sukhatme (University of Southern California), Stefanos Nikolaidis (University of Southern California) |
| ECOM | Novelty Detection and Feedback based Online Feature Subset Selection for Data Streams via Parallel Hybrid Particle Swarm Optimization Algorithm | Vivek Yelleti (National Institute of Technology Warangal, Institute for Development and Research in Banking Technology), Vadlamani Ravi (IDRBT), P. Radha Krishna (National Institute of Technology Warangal) |
| SBSE | Large Language Models as All-in-one Operators for Genetic Improvement | Gudny Birna Saemundsdottir (University of Stirling), Saemundur O. Haraldsson (University of Stirling, University of Stirling) |
| EML | Cognitive Learning System for Sequential Aliasing Patterns of States in Multistep Decision-Making | Fumito Uwano (Okayama University), Will Neil Browne (Queensland University of Technology) |
| GP | Designing Black-Box Optimizers with PushGP | Vladimir Stanovov (Siberian Federal University) |
| GA | Co-Evolutionary Learning Through Phylogeny-Informed Interaction Estimation | Jack Garbus (Brandeis University), Thomas Willkens (Brandeis University), Alexander Lalejini (Grand Valley State University), Jordan Pollack (Brandeis University) |
| GA | EMxDesign: A Genetic Algorithm for High Affinity Drug Design | Neha Jain (Georgia Institute of Technology), Andrew Hornback (Georgia Institute of Technology), May Dongmei Wang (Georgia Institute of Technology) |
| BBSR | Searching for Benchmark Problem Instances from Data-Driven Optimisation | Sara Hajari (University of Queensland), Marcus Gallagher (University of Queensland) |
| NE | A Cooperative Coevolution Neural Architecture Search Approach for Evolving Convolutional Neural Networks | Trevor Londt (Victoria University of Wellington), Xiaoying Gao (Victoria University of Wellington), Yi Mei (Victoria University of Wellington) |
| EML | An Evolutionary Approach for Exploiting Core Knowledge in Artificial Intelligence | Andrea Calabrese (Politecnico di Torino), Stefano Quer (Politecnico di Torino), Giovanni Squillero (Politecnico di Torino), Alberto Tonda (INRAE (Université Paris-Saclay), Institut des Systèmes Complexes de Paris Île-de-France) |
| BBSR | Comparing Solvability Patterns of Algorithms across Diverse Problem Landscapes | Ana Nikolikj (Jožef Stefan Institute, Jozef Stefan International Postgraduate School), Tome Eftimov (Jožef Stefan Institute) |
| RWA | Gene-level adaptation in Balanced Non-Dominated Tournament Genetic Algorithm (aB-NTGA) applied to versatile Multi-Stage Weapon-Target Assignment Problem | Michał Antkiewicz (Wroclaw University of Technology), Pawel B. Myszkowski (Wroclaw University of Science and Technology), Konrad Gmyrek (Wroclaw University of Technology) |
| ENUM | A Gradient-based Method for Differential Evolution Parameter Control by Smoothing | Haotian Zhang (Xi'an Jiaotong University), Jialong Shi (Xi'an Jiaotong University), Jianyong Sun (Xi'an Jiaotong University), Ali Wagdy Mohamed (Cairo University), Zongben Xu (Xi'an Jiaotong University) |
| SI | Matrix-Based Ant Colony Optimization | Xu Li (South China University of Technology), Min Cao (National University of Defense Technology), Jian-Yu Li (Nankai University), Jing Xu (Nankai University), Jun Zhang (Nankai University), Zhi-Hui Zhan (Nankai University) |
| EMO | A Corridor Model Evolutionary Algorithm for Fast Converging Green Vehicle Routing Problem | Ananta Anil Shahane (LIACS, Leiden University), Niki van Stein (LIACS, Leiden University), Yingjie Fan (LIACS, Leiden University) |
| RWA | Exploring Evolution for Aesthetic & Abstract 3D Art | Ritwik Murali (Amrita Vishwa Vidyapeetham), Veeramanohar Avudaiappan (Amrita Vishwa Vidyapeetham) |
| NE | Generational Information Transfer with Neuroevolution on Control Tasks | Maximilien Le Clei (Univ. de Montreal), Stav Bar-Sheshet (Tel-Aviv University), Pierre Bellec (Univ. de Montreal) |
| RWA | Evolutionary Algorithm with Cross-Generation Environmental Selection for Traveling Salesman Problem | Zi Yang Bo (Nanjing University of Information Science and Technology), Qiang Yang (Nanjing University of Information Science and Technology), Ya Hui Jia (South China University of Technology), Xu Dong Gao (Nanjing University of Information Science and Technology), Zhen Yu Lu (Nanjing University of Information Science and Technology), Jun Zhang (Nankai University) |
| ECOM | Symmetry Parallel Search Strategy For Permutation-related Optimization Problems | Tianyang Li (National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education), Ying Meng (National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education), Lixin Tang (National Frontiers Science Center for Industrial Intelligence and Systems Optimization) |
| SBSE | A Multi-Objective Genetic Algorithm for Location in Interaction Testing | Ryan Edward Dougherty (United States Military Academy), Dylan Nathan Green (United States Military Academy), Hyunmook Kang (United States Military Academy), Grace Miro Kim (United States Military Academy), Stephanie Forrest (Arizona State University) |
| GP | Feature Encapsulation by Stages Using Grammatical Evolution | Darian Reyes Fernández de Bulnes (University of Limerick), Allan de Lima (University of Limerick), Aidan Murphy (University College Dublin), Douglas Mota Dias (University of Limerick), Conor Ryan (University of Limerick) |
| EMO | Redefining the Behavior Space for Multi-Objective MAP-Elites | Anna Nickelson (Oregon State University), Kagan Tumer (Oregon State University) |
| GP | Multi-task Genetic Programming with Semantic based Crossover for Multi-output Regression | Chunyu Wang (Victoria University of Wellington), Qi Chen (Victoria University of Wellington), Bing Xue (Victoria University of Wellington), Mengjie Zhang (Victoria University of Wellington) |
| ENUM | Sensitivity Analysis of Surrogate-assisted Bilevel Optimisation | Behzad Moradi (The University of Melbourne), Michael Kirley (The University of Melbourne), Mario Andrés Muñoz Acosta (The University of Melbourne) |
| EML | Evolutionary Sparse Coding and Graph Regularisation for Embedded Multi-label Feature Selection | Kaan Demir (Victoria University of Wellington), Bach Nguyen (Victoria University of Wellington), Bing Xue (Victoria University of Wellington), Mengjie Zhang (Victoria University of Wellington) |
| RWA | Evolutionary Algorithm Based Adaptive Image Anonymization | Arcadi Llanza (University Paris Est Créteil, Laboratoire LISSI, Cyclope.ai), Nadiya Shvai (Cyclope.ai, National University of Kyiv-Mohyla Academy), Amir Nakib (University Paris Est Créteil, Laboratoire LISSI, Cyclope.ai) |
| GECH | Variable Contribution-Based Differential Evolution for Large-Scale Global Optimization | ErJie Tian (Jiangnan University), Jian Yao (Jiangnan University), Wei Fang (Jiangnan University), Pengjiang Qian (Jiangnan University), Xin Zhang (Jiangnan University) |
| SBSE | Dynamic Difficulty Coefficient in Search-Based Software Testing: Targeting to Hard Branch Coverage | Thi-Mai-Anh BUI (HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY, School of Information and Communication Technology), Van-Tri DO (Hanoi University of Science and Technology, School of Information and Communication Technology), Minh Vu Le (Hanoi University of Science and Technology, School of Information and Communication Technology), Quoc-Trung BUI (Hanoi University of Science and Technology, School of Information and Communication Technology) |
| NE | AD-NEv++ - The multi-architecture neuroevolution-based multivariate anomaly detection framework | Marcin Pietroń (AGH University of Krakow), Dominik Żurek (AGH University of Krakow), Kamil Faber (AGH University of Krakow), Anna Wójcik (AGH University of Krakow), Roberto Corizzo (American University) |
| EML | Length-niching Selection and Spatial Crossover in Variable-length Evolutionary Rule Set Learning | David Pätzel (University of Augsburg), Richard Nordsieck (XITASO GmbH IT & Software Solutions), Jörg Hähner (University of Augsburg) |
| L4EC | Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization | Carolin Benjamins (Leibniz University Hannover), Gjorgjina Cenikj (Jožef Stefan Institute), Ana Nikolikj (Jožef Stefan Institute), Aditya Mohan (Leibniz University Hannover), Tome Eftimov (Jožef Stefan Institute), Marius Lindauer (Leibniz University Hannover) |
| EMO | Multi-Objective Evolution for Chemical Product Design | Geoff Nitschke (University of Cape Town), Bilal Aslan (University of Cape Town), Flavio da Silva (Sao Paulo State University) |
| GP | A Comprehensive Analysis of Down-sampling for Genetic Programming-based Program Synthesis | Ryan Boldi (University of Massachusetts Amherst), Ashley Bao (Amherst College), Martin Briesch (Johannes Gutenberg-Universität), Thomas Helmuth (Hamilton College), Dominik Sobania (Johannes Gutenberg-Universität), Lee Spector (Amherst College), Alexander Lalejini (Grand Valley State University) |
| NE | Neural Loss Function Evolution for Large-Scale Image Classifier Convolutional Neural Networks | Brandon Morgan (University of Oklahoma), Dean Hougen (University of Oklahoma) |
| EMO | Simple Distributed Bit Climber for Many-objective Optimization of Binary Epistatic Problems | Yudai Tagawa (Shinshu University), Hernan Aguirre (Shinshu University), Kiyoshi Tanaka (Shinshu University) |
| GECH | A Multi-Fitness Meta-Evolutionary Algorithm for Cellular Automata via Evolved Generative Genotype to Phenotype Mappings | Nathan Gaylinn (University of Vermont), Joshua Bongard (University of Vermont) |
| EMO | Multi-population for Multi-objective Genetic Algorithm with Adaptive Information Sharing Strategy for Berth Allocation and Quay Crane Assignment Problems | Wanqiu Zhao (Xi'an Jiaotong University), Qi Qiu (Xidian University), Hong Zhao (Xidian University), Xu Bian (Xi'an Jiaotong University), He Yu (Xidian University), Jing Liu (Xidian University), Xuesong Mei (Xi'an Jiaotong University) |
| ECOM | Distributed Ensemble Hyper-Heuristic Algorithm for Aircraft Arrival Sequencing and Scheduling Problem | Xian-Ping Wang (South China University of Technology), Xin-Xin Xu (Ocean University of China), Yi Jiang (South China University of Technology), Sheng Bi (South China University of Technology), Yan-Chun Liang (Zhuhai College of Science and Technology), Zhi-Hui Zhan (Nankai University) |
| GA | Genetic Algorithm with Modified Reproduction Operators for Grammatical Inference | Hari Mohan Pandey (Bournemouth University) |
| SI | ClientShield: Malicious Clients Avoidance in Federated Learning with the Help of an Ant | Somonindro Roy (Bangladesh University of Engineering and Technology), Md. Shahrukh Islam (Bangladesh University of Engineering and Technology), Md Adnan Arefeen (University of Missouri), Muhammad Ali Nayeem (Bangladesh University of Engineering and Technology) |
| GP | EXA-GP: Unifying Graph-Based Genetic Programming and Neuroevolution for Explainable Time Series Forecasting | Jared Murphy (Rochester Institute of Technology), Devroop Kar (Rochester Institute of Technology), Joshua Karns (Rochester Institute of Technology), Travis Desell (Rochester Institute of Technology) |
| RWA | Particle Swarm Optimization Meets Deep Learning for Estimating Root-Zone Soil Moisture from Hyperspectral Images | Bogdan Ruszczak (Opole University of Technology), Michał Myller (Silesian University of Technology), Łukasz Tulczyjew (Silesian University of Technology), Agata M. Wijata (Silesian University of Technology), Jakub Nalepa (Silesian University of Technology) |
| SBSE | Local Search-based Approach for Cost-effective Job Assignment on Large Language Models | Yueyue Liu (The University of Newcastle), Hongyu Zhang (Chongqing University), Van-Hoang Le (The University of Newcastle), Yuantian Miao (The University of Newcastle), Zhiqiang Li (Shaanxi Normal University) |
| EML | Lexidate: Model Evaluation and Selection with Lexicase | Jose Guadalupe Hernandez (Cedars-Sinai Medical Center), Anil Kumar Saini (Cedars-Sinai Medical Center), Jason Hall Moore (Cedars-Sinai Medical Center) |
| SBSE | Evolving Assembly Code in an Adversarial Environment | Irina Maliukov (Ben-Gurion University), Gera Weiss (Ben-Gurion University), Oded Margalit (Ben-Gurion University), Achiya Elyasaf (Ben-Gurion University) |
| NE | Improved Brain Tumor Segmentation Using Modified U-Net based on Particle Swarm Optimization Image Enhancement | Shoffan Saifullah (Faculty of Computer Science, AGH University of Krakow, Poland, Department of Informatics, Universitas Pembangunan Nasional Veteran Yogyakarta, Indonesia), Rafał Dreżewski (Faculty of Computer Science, AGH University of Krakow, Poland) |
| GA | Investigating Structural Bias in Real-Coded Genetic Algorithms | Kanchan Rajwar (Indian Institute of Technology Roorkee), Yogesh Kumar (Indian Institute of Technology Roorkee), Kusum Deep (Indian Institute of Technology Roorkee) |
| ECOM | Randomized Local Search on the 2D Rectangular Bin Packing Problem with Item Rotation | Rui Zhao (Hefei University/Institute of Applied Optimization), Tianyu Liang (Hefei University/Institute of Applied Optimization), Zhize Wu (Hefei University/Institute of Applied Optimization), Daan van den Berg (VU University Amsterdam), Matthias Thürer (TU Chemnitz), Thomas Weise (Hefei University/Institute of Applied Optimization) |
| GP | Greedy Strategies to Improve Phased Genetic Programming When Applied Directly to the Traveling Salesman Problem | Darren M. Chitty (University of Exeter), Ed Keedwell (University of Exeter) |
| SBSE | Enhancing Fault Detection in Smart Contract Loops Through Adaptive Probabilistic Sampling | Stuart Dereck Semujju (South China University of Technology), Fangqing Liu (South China University of Technology), Han Huang (South China University of Technology), Yi Xiang (South China University of Technology) |
| EML | Shifting Color Space for Image Classification using Genetic Programming | David Herrera-Sánchez (University of Veracruz), Héctor-Gabriel Acosta-Mesa (University of Veracruz), Efrén Mezura-Montes (University of Veracruz), Aldo Márquez-Grajales (University of Veracruz) |
| BBSR | Extending Instance Space Analysis to Algorithm Configuration Spaces | Anthony Rasulo (The University of Melbourne, The University of Manchester), Kate Smith-Miles (The University of Melbourne), Mario Andrés Muñoz (The University of Melbourne), Julia Handl (The University of Manchester), Manuel López-Ibáñez (The University of Manchester) |
| RWA | Exploring a Small Molecule Property Prediction Model with Optimal Comprehensive Performance through Multi-Objective Optimization Algorithms | Junfeng Zhao (Northeastern University), Lixin Tang (Northeastern University), Yong Shuai (Xinyu Iron & Steel Co., Ltd.) |
| EML | Instance-Label Based Multi-Label Active Learning by Evolutionary Multi-Objective Optimization | Yuheng Zhou (Nanjing University), Haopu Shang (Nanjing University), Yu-Chang Wu (Nanjing University), Chao Qian (Nanjing University) |
| RWA | Many-Objective Evolutionary Influence Maximization: Balancing Spread, Budget, Fairness, and Time | Elia Cunegatti (University of Trento), Leonardo Lucio Custode (University of Trento), Giovanni Iacca (University of Trento) |
| BBSR | A Multi-objective Optimization Benchmark Test Suite for Real-time Semantic Segmentation | Yifan Zhao (Southern University of Science and Technology), Zhenyu Liang (Southern University of Science and Technology), Zhichao Lu (City University of Hong Kong), Ran Cheng (Southern University of Science and Technology) |
| EML | Time-varying Echo State Networks: Harnessing Dynamic Parameters for Robust Time-Series Analysis | Nabangshu Sinha (University of Camerino), Carlo Lucheroni (University of Camerino) |
| ECOM | Estimating the Number of Local Optima in Multimodal Pseudo-Boolean Functions: Validation via Landscapes of Triangles | Xavier F. C. Sánchez-Díaz (Norwegian University of Science and Technology), Ole Mengshoel (Norwegian University of Science and Technology, Carnegie Mellon University) |
| GA | Hypernetwork-Based Multi-Objective Optimization with NSGA-II | Jie He (National University of Defense Technology), Yaohong Zhang (National University of Defense Technology), Ji Wang (National University of Defense Technology), Xiaoqing Li (National University of Defense Technology), Weidong Bao (National University of Defense Technology) |
| EMO | Visualization of Multi-objective Multimodal Benchmarking Based on Basin Connectivity | Likun Liu (Kyushu University), Ryosuke Ota (Kyushu University), Takahiro Yamamoto (Tokyo Gakugei University), Naoki Hamada (KLab Inc.), Daisuke Sakurai (Fujitsu Research Institute, Kyushu University) |
| EML | LLM-POET: Evolving Complex Environments using Large Language Models | Fuma Aki (University of Tsukuba), Riku Ikeda (University of Tsukuba), Takumi Saito (University of Tsukuba), Ciaran Regan (University of Tsukuba), Mizuki Oka (University of Tsukuba) |
| EML | Onboard Class Incremental Learning for Resource-Constrained scenarios using Genetic Algorithm and TinyML | Suraj Kumar Pandey (Indian Institute of Technology Guwahati), Shivashankar B. Nair (Indian Institute of Technology Guwahati) |
| GA | Implicit Symbolic Regression via Probabilistic Fitness | Graham Roberts (University of Connecticut), Everett Grethel (University of Connecticut), Qian Yang (University of Connecticut) |
| BBSR | Multi-objective Ranking using Bootstrap Resampling | Jeroen Rook (University of Twente), Holger H. Hoos (RTWH Aachen, Leiden University), Heike Trautmann (University of Paderborn, University of Twente) |
| SI | Tensorized Ant Colony Optimization for GPU Acceleration | Luming Yang (Southern University of Science and Technology), Tao Jiang (Southern University of Science and Technology, Pengcheng Laboratory), Ran Cheng (Southern University of Science and Technology) |
| RWA | A Memetic Algorithm to Identify Search Patterns for Maximal Coverage of Drifting Oceanic Particles | So-Jung Lee (Kwangwoon Univ.), Yong-Hyuk Kim (Kwangwoon Univ.) |
| EML | an Interpretable Clustering Method Based on Data Topology | Matthew Vandergrift (Queen's University), Ting Hu (Queen's University) |
| L4EC | Online Per-Instance Algorithm Selection for Constrained Multi-Objective Optimization Problems | Hanan Alsouly (The University of Melbourne), Michael Kirley (The University of Melbourne), Mario Andrés Muñoz (The University of Melbourne) |
| EMO | Evolutionary Optimization using Density Peaks Scoring Selection Strategy | Siamak Ghodsi (Free University of Berlin), Sahar Tahmasebi (TIB – Leibniz Information Centre for Science and Technology), Mahdi Jalili (RMIT University), Parham Moradi (RMIT University, University of Kurdistan) |
| L4EC | Per-Run Algorithm Performance Improvement Forecasting Using Exploratory Landscape Analysis Features: A Case Study in Single-Objective Black-Box Optimization | Peter Korošec (Jožef Stefan Institute), Tome Eftimov (Jožef Stefan Institute) |
| EML | Multidimensional Archive Of The State Space | Joshua Cook (Oregon State University), Kagan Tumer (Oregon State University) |
| EMO | Differential Evolution based on Local Grid Search for Multimodal Multiobjective Optimization with Local Pareto Fronts | Juan Zou (Xiangtan University), TianBin Xie (Xiangtan University), Qi Deng (Xiangtan University), XiaoZhong Yu (Xiangtan University), ShengXiang Yang (De Montfort University), JinHua Zheng (Xiangtan University) |
| GA | Evolving Weighted and Directed Graphs with Constrained Properties | Sydney Leither (Michigan State University), Vincent R. Ragusa (Michigan State University), Emily Dolson (Michigan State University) |
| RWA | Solving Indefinite Communication Reliability Optimization for RIS-Aided Mobile Systems by an Improved Differential Evolution | Trinh Van Chien (Hanoi University of Science and Technology), Bui Trong Duc (Hanoi University of Science and Technology), Duc Luong Viet Ho (Hanoi University of Science and Technology), Huynh Thi Thanh Binh (Hanoi University of Science and Technology), Hien Quoc Ngo (Queen's University Belfast), Symeon Chatzinotas (Université du Luxembourg) |
| RWA | LVNS-RAVE: Diversified audio generation with RAVE and Latent Vector Novelty Search | Jinyue Guo (University of Oslo), Anna-Maria Christodoulou (University of Oslo), Balint Laczko (University of Oslo), Kyrre Glette (University of Oslo) |
| EML | Generalizing Diversity with the Signature Transform | Arno Feiden (Fraunhofer SCAI, Institut für Numerische Simulation / Universität Bonn), Biagio Paparella (Institut für Numerische Simulation / Universität Bonn), Jochen Garcke (Institut für Numerische Simulation / Universität Bonn, Fraunhofer SCAI) |
| GECH | Adaptive Immune Optimization Algorithm: Combining Mutual Information and Differential Evolution-based Mutation for Local Feature Selection on Microarray Data | Yi Wang (Hubei University of Economics), Wenshan Li (Chengdu University of Information Technology), Tao Li (Sichuan University) |
| EML | Efficient Edge Computing: Harnessing Compact Machine Learning Models for Workload Optimization | Mohammad Reza Pour-Hosseini (Bu-Ali Sina University), Mahdi Abbasi (Aix-Marseille Université,, Bu-Ali Sina University), Bahman Javadi (Western Sydney University), Seifeddine BenElghali (Aix-Marseille Université), Hassan Haghighi (Aix-Marseille Université), Ehsan Mohammadi-Pasand (Bu-Ali Sina University), Parham Moradi (RMIT University) |
| GA | Exploring Knowledge Transfer in Evolutionary Many-task Optimization: A Complex Network Perspective | Yudong Yang (Xidian University), Kai Wu (Xidian University), Xiangyi Teng (Xidian University), Handing Wang (Xidian University), He Yu (Xidian University), Jing Liu (Xidian University) |
| GP | Multimodal Adaptive Graph Evolution | Camilo De La Torre (University of Toulouse, IRIT), Kévin Cortacero (University of Toulouse, IRIT), Sylvain Cussat-Blanc (University of Toulouse, IRIT), Dennis Wilson (ISAE-SUPAERO, University of Toulouse) |
| EML | Exploring Evolutionary Generators within Generative Adversarial Networks | Francisco Baeta (University of Coimbra), João Correia (University of Coimbra), Tiago Martins (University of Coimbra), Penousal Machado (University of Coimbra) |
| RWA | Evaluation of Genetic Algorithms in Multi-Vehicle Control for Multi-Target Tracking Applications | Aidan Blair (RMIT University), Amirali Khodadadian Gostar (RMIT University), Xiaodong Li (RMIT University), Alireza Bab-Hadiashar (RMIT University), Reza Hoseinnezhad (RMIT University) |
| EML | Evolving Visual Counterfactual Medical Imagery Explanations with Cooperative Co-evolution using Dynamic Decomposition | Luke Brendan Kelly (Edith Cowan University), Martin Masek (Edith Cowan University), Chiou Peng Lam (Edith Cowan University), Brandon Abela (Edith Cowan University), Ashu Gupta (Fiona Stanley Hospital) |
| GP | Guiding Genetic Programming with Graph Neural Networks | Piotr Wyrwiński (Poznan University of Technology), Krzysztof Krawiec (Poznan University of Technology) |
| BBSR | Ealain: A Camera Simulation Tool to Generate Instances for Multiple Classes of Optimisation Problem | Quentin Renau (Edinburgh Napier University), Johann Dreo (Institut Pasteur), Emma Hart (Edinburgh Napier University) |
| ECOM | Emergence of Strategies for Univariate Estimation-of-Distribution Algorithms with Evolved Neural Networks | Olivier Goudet (LERIA, University of Angers), Adrien Goëffon (LERIA, University of Angers), Frédéric Saubion (LERIA, University of Angers), Sébastien Verel (LISIC, Université du Littoral Côte d'Opale) |
| GP | Fast Self-Learning of Turbulence Feedback Laws Using Gradient-Enriched Machine Learning Control | Guy Y. Cornejo Maceda (Harbin Institute of Technology, Shenzhen), Zhutao Jiang (Harbin Institute of Technology, Shenzhen), François Lusseyran (Laboratoire interdisciplinaire des sciences du numérique), Bernd R. Noack (Harbin Institute of Technology, Shenzhen) |
| RWA | A Micro Dynamic Multi-objective Evolutionary Algorithm for Small-scale Smart Greenhouse with Low-power Microprocessor | Zhongtian Luo (Jiujiang University), Jianpeng Xiong (Jiujiang University), Hu Peng (Jiujiang University), Gaosheng Zhan (Jiujiang University), Qingfu Zhang (City University of Hong Kong), Hui Wang (Nanchang Institute of Technology), Xinyu Zhou (Jiangxi Normal University), Wei Li (Jiangxi University of Science and Technology), Ying Huang (Gannan Normal University) |
| CS | Growing Artificial Neural Networks for Control: the Role of Neuronal Diversity | Eleni Nisioti (IT University of Copenhagen), Erwan Plantec (IT University of Copenhagen), Milton Llera Montero (IT University of Copenhagen), Joachim Winther Pedersen (IT University of Copenhagen), Sebastian Risi (IT University of Copenhagen) |
| RWA | Evolutionary Ensemble for Predicting Drifter Trajectories Based on Genetic Feature Selection | Tae-Hoon Kim (Kwangwoon Univ.), Seung-Hyun Moon (Kwangwoon Univ.), Yong-Hyuk Kim (Kwangwoon Univ.) |
| EML | Intepretable Local Explanations Through Genetic Programming | Hayden Andersen (Victoria University of Wellington), Andrew Lensen (Victoria University of Wellington), Will Browne (Queensland University of Technology), Yi Mei (Victoria University of Wellington) |
| ECOM | Local Search Algorithms for the Oven Scheduling Problem | Francesca Da Ros (Università degli Studi di Udine, Intelligent Optimization Lab), Luca Di Gaspero (Università degli Studi di Udine, Intelligent Optimization Lab), Marie-Louise Lackner (TU Wien, Christian Doppler Laboratory), Nysret Musliu (TU Wien, Christian Doppler Laboratory), Felix Winter (TU Wien, Christian Doppler Laboratory) |
| ENUM | A Combination of CMA-ES with Probability Distributions of Integer Variables for Mixed-Integer Black-Box Optimization | Duc Manh Nguyen (Hanoi National University of Education) |
| ECOM | Memetic Algorithm for Multi-objective Virtual Network Slice Configuration | Qinan Chen (Southern University of Science and Technology), Qiqi Xia (Southern University of Science and Technology), Kaixuan Sun (Southern University of Science and Technology), Jin Wang (Huawei), Bo Yuan (Southern University of Science and Technology) |
| GP | Introducing Vectorized Cluster Crossover in Grammatical Evolution | Michał Kowalczykiewicz (Computational Intelligence Research Group, Institute of Computer Science, University of Wroclaw), Piotr Lipiński (Computational Intelligence Research Group, Institute of Computer Science, University of Wroclaw) |
| GP | A Preliminary Counterfactual Explanation Method for Genetic Programming-Evolved Rules: A Case Study on Uncertain Capacitated Arc Routing Problem | Shaolin Wang (Zhejiang Geely Holding Group, Victoria University of Wellington), Yi Mei (Victoria University of Wellington), Mengjie Zhang (Victoria University of Wellington) |
| GP | Dynamically Sampling biomedical Images For Genetic Programming Ensembles | Yuri Lavinas (University of Toulouse), Nathaniel Haut (Michigan State University), William Punch (Michigan State University), Wolfgang Banzhaf (Michigan State University), Sylvain Cussat-Blanc (University of Toulouse) |
| GECH | Dynamic Quality-Diversity Search | Roberto Gallotta (University of Malta), Antonios Liapis (University of Malta), Georgios N. Yannakakis (University of Malta) |
| NE | Quality Diversity for Robot Learning: Limitations and Future Directions | Sumeet Batra (University of Southern California), Bryon Tjanaka (University of Southern California), Stefanos Nikolaidis (University of Southern California), Gaurav Sukhatme (University of Southern California) |
| BBSR | Learning to Generate Scalable MILP Instances | Tianxing Yang (Tsinghua University, Sun Yat-sen University), Huigen Ye (Tsinghua University), Hua Xu (Tsinghua University) |
| EMO | The Optimal Zone Breadth for Parallel and Distributed MOEA/D with Virtual Overlap Zone and Exclusively Evaluated Mating | XINYUAN ZHU (Hosei University), Yuji Sato (Hosei University), Mikiko Sato (Tokai University) |
| GP | Decomposition-based Multi-objective Genetic Programming for Feature Learning in Image Classification | Tuo Zhang (Zhengzhou University), Ying Bi (Zhengzhou University), Jing Liang (Zhengzhou University), Bing Xue (Victoria University of Wellington), Mengjie Zhang (Victoria University of Wellington) |
| ENUM | TransOptAS: Transformer-Based Algorithm Selection for Single-Objective Optimization | Gjorgjina Cenikj (Jožef Stefan Institute, Ljubljana, Slovenia, Jožef Stefan International Postgraduate School), Gašper Petelin (Jožef Stefan Institute, Jožef Stefan International Postgraduate School), Tome Eftimov (Jožef Stefan Institute) |
| RWA | Survival Strategies for Evolutionary Role Mining Algorithms Using Expert Knowledge | Simon Anderer (SIVIS GmbH), Nicolas Justen (SIVIS GmbH), Bernd Scheuermann (Karlsruhe University of applied Sciences), Sanaz Mostaghim (Otto von Guericke University Magdeburg) |
| SI | A new Hybrid Parameter Independent Particle Swarm Optimization Algorithm | Piotr Dziwiński (Czestochowa University of Technology) |
| ECOM | PEACH: A Multi-Objective Evolutionary Algorithm for Complex Vehicle Routing with Three-Dimensional Loading Constraints | Han Zhang (Southern University of Science and Technology, The Hong Kong Polytechnic University), Qing Li (The Hong Kong Polytechnic University), Xin Yao (Lingnan University) |
| EML | Behaviour Discovery in Real-Time Strategy Games using Cooperative Co-evolution with Dynamic Binary Tree Decomposition | Luke Brendan Kelly (Edith Cowan University), Martin Masek (Edith Cowan University), Chiou Peng Lam (Edith Cowan University) |
| GP | Multi-objective multi-population Genetic Programming for feature selection and classification to high-dimensional data | Qiaoman Li (Hebei Agricultural University), Xiaoying Gao (Victoria University of Wellington), Wenyang Meng (Hebei Agricultural University), Jianbin Ma (Hebei Agricultural University) |
| GP | Synergistic Utilization of LLMs for Program Synthesis | David Vella Zarb (University of Cambridge), Geoff Parks (University of Cambridge), Timoleon Kipouros (University of Cambridge) |
| EMO | A Dynamic Preference-driven Evolutionary Algorithm for Solving Dynamic Multi-objective Problems | XueQing Wang (Xiangtan University), JinHua Zheng (Xiangtan University), Juan Zou (Xiangtan University), ZhangLu Hou (Xiangtan University), ShengXiang Yang (De Montfort University), Yuan Liu (Xiangtan University) |
| NE | Satellite Image based Crop Classification Using Convolutional Autoencoder | Aswitha Tadepalli (Indian Institute of Technology Hyderabad), Kishalay Mitra (Indian Institute of Technology Hyderabad) |
| L4EC | Mining Potentially Explanatory Patterns via Partial Solutions | GianCarlo Antonino Pasquale Ignazio Catalano (University of Stirling), Alexander E. I. Brownlee (University of Stirling), David Cairns (University of Stirling), John McCall (national Subsea Centre, Robert Gordon University), Russell Ainslie (BT Technology) |
| EMO | A Competitive Swarm Algorithm Based on Tri-Competitive Criterion for Constrained Multiobjective Optimization | jinlong zhou (Central South University), Yinggui Zhang (Central South University), Fan Yu (Central South University) |
| CS | Looking for Complexity at Phase Boundaries in Continuous Cellular Automata | Vassilis Papadopoulos (EPFL), Guilhem Doat (EPFL), Arthur Renard (EPFL), Clément Hongler (EPFL) |
| NE | Analysis of Pruned Deep Models Trained with Neuroevolution | Federico Da Rold (Ochanomizu University, Cross Labs, Cross Compass ltd.), Leo Cazenille (Université Paris Cité, CNRS, LIED UMR 8236), Nathanael Aubert-Kato (Ochanomizu University) |
| ENUM | On Generalization of ELA Feature Groups | Gašper Petelin (Jozef Stefan Institute, Jožef Stefan International Postgraduate School), Gjorgjina Cenikj (Jožef Stefan Institute, Jožef Stefan International Postgraduate School) |
| RWA | Evolution of Material Properties and Gripping Strategy in Soft Robotic Jamming Devices | Seth Fitzgerald (CSIRO, Data61, Queensland University of Technology), Sarah Baldwin (CSIRO, Data61), David Howard (CSIRO, Data61), Frederic Maire (Queensland University of Technology), Gary W. Delaney (CSIRO, Data61) |
| EMO | Lower Confidence Bound for Preference Selection in Interactive Multi-Objective Optimization | Arash Heidari (Ghent University, imec), Sebastian Rojas Gonzalez (Ghent University, Hasselt University), Tom Dhaene (Ghent University, imec), Ivo Couckuyt (Ghent University, imec) |
| NE | Exploring Layerwise Adversarial Robustness Through the Lens of t-SNE | Inês Valentim (University of Coimbra, CISUC/LASI, DEI), Nuno Antunes (University of Coimbra, CISUC/LASI, DEI), Nuno Lourenço (Coimbra) |
| GP | A Comparison of Feature Engineering Techniques for Hearing Loss | Miguel Rabuge (University of Coimbra, CISUC/LASI, DEI), Nuno Lourenço (Coimbra) |
| EMO | Multi-population models based on evolutionary algorithms have been successfully applied to countless feature selection problems. One of the most relevant aspects is the initialization of the individuals that form the initial population, where any bias should be avoided. Usually, the initial individuals are randomly generated with the aid of the Pf hyperparameter (the selection probability for any feature when generating an individual of the initial population). Pf is usually set to 0.5 (the same chance of selecting or not any feature). However, different values for this hyperparameter may influence the results finally found and the execution time and energy consumed by the algorithm. This paper analyzes the behavior of a multi-objective and multi-population procedure when setting Pf to different values for several datasets. The results show that there is an optimal value of Pf for each dataset that speeds up the process without affecting the quality of the solutions, in addition to reducing the size of the final subset of features in some cases. | Juan Carlos Gómez-López (Granada), Daniel Castillo-Secilla (Fujitsu Technology Solutions S.A., CoE Data Intelligence), Jesús González (CITIC, University of Granada) |
| BBSR | Benchmark Problems for Machine Learning in Control Synthesis | Elizaveta Shmalko (Federal Research Center Computer Science and Control of the Russian Academy of Sciences), Askhat Diveev (Federal Research Center Computer Science and Control of the Russian Academy of Sciences) |