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ORCIDGECCO 2024: Melbourne, VIC, Australia
- Xiaodong Li, Julia Handl:
Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024. ACM 2024
Keynote Talk
- Una-May O'Reilly:
Coevolution in Natural and Artificial Systems. - Suzie Sheehy:
Lessons from curiosity-driven physics research. - Toby Walsh:
Generative AI: why all the fuss?
Benchmarking, Benchmarks, Software and Reproducibility
- Ali Ahrari, Jonathan E. Fieldsend, Mike Preuss, Xiaodong Li, Michael Epitropakis:
New Tunable Test Problems for Benchmarking Niching Methods for Multimodal Optimization. - Roman Kalkreuth, Thomas Bäck:
CGP++ : A Modern C++ Implementation of Cartesian Genetic Programming. - Cedric J. Rodriguez, Sarah L. Thomson, Tanja Alderliesten, Peter A. N. Bosman:
Temporal True and Surrogate Fitness Landscape Analysis for Expensive Bi-Objective Optimisation. - Thai Bao Tran, Ngoc Hoang Luong:
On the Investigation of Multimodal Evolutionary Algorithms Using Search Trajectory Networks. - Diederick Vermetten, Carola Doerr, Hao Wang, Anna V. Kononova, Thomas Bäck:
Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics. - Danial Yazdani, Juergen Branke, Mohammad Sadegh Khorshidi, Mohammad Nabi Omidvar, Xiaodong Li, Amir H. Gandomi, Xin Yao:
Clustering in Dynamic Environments: A Framework for Benchmark Dataset Generation With Heterogeneous Changes. - Yuanting Zhong, Xincan Wang, Yuhong Sun, Yue-Jiao Gong:
SDDObench: A Benchmark for Streaming Data-Driven Optimization with Concept Drift.
Complex Systems
- Timothée Anne, Jean-Baptiste Mouret:
Parametric-Task MAP-Elites. - Kameron Bielawski, Nate Gaylinn, Cameron Lunn, Kevin Motia, Joshua Bongard:
Evolving Hierarchical Neural Cellular Automata. - Andrea Ferigo, Elia Cunegatti, Giovanni Iacca:
Neuron-centric Hebbian Learning. - Tanja Katharina Kaiser:
Learning from Evolution: Improving Collective Decision-Making Mechanisms using Insights from Evolutionary Robotics. - Paul Templier, Luca Grillotti, Emmanuel Rachelson, Dennis Wilson, Antoine Cully:
Quality with Just Enough Diversity in Evolutionary Policy Search. - Sarah L. Thomson, Léni K. Le Goff, Emma Hart, Edgar Buchanan:
Understanding Fitness Landscapes in Morpho-Evolution via Local Optima Networks. - Wen-Chi Yang:
Integrating Diverse Evolutionary Patterns of Collective Animal Behaviours into a Unified Selfish Herd Model.
Evolutionary Combinatorial Optimization and Metaheuristics
- Jakob Bossek, Christian Grimme:
Generalised Kruskal Mutation for the Multi-Objective Minimum Spanning Tree Problem. - Maria Bresich, Günther R. Raidl, Steffen Limmer:
Letting a Large Neighborhood Search for an Electric Dial-A-Ride Problem Fly: On-The-Fly Charging Station Insertion. - Camilo Chacón Sartori, Christian Blum, Gabriela Ochoa:
An Extension of STNWeb Functionality: On the Use of Hierarchical Agglomerative Clustering as an Advanced Search Space Partitioning Strategy. - Camilo Chacón Sartori, Christian Blum, Gabriela Ochoa:
Large Language Models for the Automated Analysis of Optimization Algorithms. - Benjamin Doerr, Martin S. Krejca, Nguyen Vu:
Superior Genetic Algorithms for the Target Set Selection Problem Based on Power-Law Parameter Choices and Simple Greedy Heuristics. - Cheng Gong, Yang Nan, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang:
Heuristic Initialization and Knowledge-based Mutation for Large-Scale Multi-Objective 0-1 Knapsack Problems. - Ishara Hewa Pathiranage, Frank Neumann, Denis Antipov, Aneta Neumann:
Effective 2- and 3-Objective MOEA/D Approaches for the Chance Constrained Knapsack Problem. - Kyo Kuroki, Satoru Jimbo, Thiem Van Chu, Masato Motomura, Kazushi Kawamura:
Classical Thermodynamics-based Parallel Annealing Algorithm for High-speed and Robust Combinatorial Optimization. - Alejandro Marrero, Eduardo Segredo, Coromoto León, Emma Hart:
Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution. - Thilina Pathirage Don, Aneta Neumann, Frank Neumann:
The Chance Constrained Travelling Thief Problem: Problem Formulations and Algorithms. - Kokila Kasuni Perera, Aneta Neumann:
Multi-Objective Evolutionary Algorithms with Sliding Window Selection for the Dynamic Chance-Constrained Knapsack Problem. - Quan Minh Phan, Ngoc Hoang Luong:
Efficient Multi-Fidelity Neural Architecture Search with Zero-Cost Proxy-Guided Local Search. - Valentino Santucci, Marco Baioletti, Marco Tomassini:
Optimization through Iterative Smooth Morphological Transformations. - Han Zhang, Qing Li, Xin Yao:
An Adaptive Interactive Routing-Packing Strategy for Split Delivery Vehicle Routing Problem with 3D Loading Constraints.
Evolutionary Machine Learning
- Pivithuru Thejan Amarasinghe, Diem Pham, Binh Tran, Su Nguyen, Yuan Sun, Damminda Alahakoon:
Evolutionary Multi-Objective Optimisation for Fairness-Aware Self Adjusting Memory Classifiers in Data Streams. - Pedro Barbosa, Rosina Savisaar, Alcides Fonseca:
Semantically Rich Local Dataset Generation for Explainable AI in Genomics. - Amanda Bertschinger, James P. Bagrow, Joshua Clifford Bongard:
Evolving Form and Function: Dual-Objective Optimization in Neural Symbolic Regression Networks. - Joshua Cook, Kagan Tumer:
Learning Aligned Local Evaluations For Better Credit Assignment In Cooperative Coevolution. - Leonardo Lucio Custode, Ivanoe De Falco, Antonio Della Cioppa, Giovanni Iacca, Umberto Scafuri:
NEvoFed: A Decentralized Approach to Federated NeuroEvolution of Heterogeneous Neural Networks. - Hangqi Ding, Haoran Xu, Yue Wu, Hao Li, Maoguo Gong, Wenping Ma, Qiguang Miao, Jiao Shi, Yu Lei:
Evolutionary Multitasking with Two-level Knowledge Transfer for Multi-view Point Cloud Registration. - Gaurav Dixit, Kagan Tumer:
Informed Diversity Search for Learning in Asymmetric Multiagent Systems. - Everardo Gonzalez, Siddarth Viswanathan, Kagan Tumer:
Influence Based Fitness Shaping for Coevolutionary Agents. - Erik Hemberg, Una-May O'Reilly, Jamal Toutouh:
Cooperative Coevolutionary Spatial Topologies for Autoencoder Training. - Angus Kenny, Tapabrata Ray, Steffen Limmer, Hemant Kumar Singh, Tobias Rodemann, Markus Olhofer:
Using Bayesian Optimization to Improve Hyperparameter Search in TPOT. - Yi Liu, Yu Cui, Wen Cheng, Will Neil Browne, Bing Xue, Chengyuan Zhu, Yiding Zhang, Mingkai Sheng, Lingfang Zeng:
A Phenotypic Learning Classifier System for Problems with Continuous Features. - Zeqiong Lv, Chao Bian, Chao Qian, Yanan Sun:
Runtime Analysis of Population-based Evolutionary Neural Architecture Search for a Binary Classification Problem. - Alican Mertan, Nick Cheney:
Towards Multi-Morphology Controllers with Diversity and Knowledge Distillation. - Clint Morris, Michael Jurado, Jason Zutty:
LLM Guided Evolution - The Automation of Models Advancing Models. - Shuaiqun Pan, Diederick Vermetten, Manuel López-Ibáñez, Thomas Bäck, Hao Wang:
Transfer Learning of Surrogate Models via Domain Affine Transformation. - Nian Ran, Bahrul Ilmi Nasution, Claire Little, Richard Allmendinger, Mark J. Elliot:
Multi-objective evolutionary GAN for tabular data synthesis. - Erdi Sayar, Giovanni Iacca, Alois Knoll:
Multi-Objective Evolutionary Hindsight Experience Replay for Robot Manipulation Tasks. - Lukasz Tulczyjew, Michal Przewozniczek, Renato Tinós, Agata M. Wijata, Jakub Nalepa:
CANNIBAL Unveils the Hidden Gems: Hyperspectral Band Selection via Clustering of Weighted Variable Interaction Graphs. - Jiahong Wei, Bing Xue, Mengjie Zhang:
EZUAS: Evolutionary Zero-shot U-shape Architecture Search for Medical Image Segmentation. - Alexa A. Woodward, Harsh Bandhey, Jason H. Moore, Ryan J. Urbanowicz:
Survival-LCS: A Rule-Based Machine Learning Approach to Survival Analysis. - Michal Wójcik, Milosz Kadzinski:
Nature-inspired Preference Learning Algorithms Using the Choquet Integral. - Jiang Zhu, Hong Zhao, He Yu, Jing Liu:
Pixel Logo Attack: Embedding Attacks as Logo-Like Pixels.
Evolutionary Multiobjective Optimization
- Andrejaana Andova, Jordan N. Cork, Tea Tusar, Bogdan Filipic:
Enhancing Algorithm Performance Prediction in Constrained Multiobjective Optimization Using Additional Training Problems. - Denis Antipov, Aneta Neumann, Frank Neumann:
A Detailed Experimental Analysis of Evolutionary Diversity Optimization for OneMinMax. - Longcan Chen, Lie Meng Pang, Qingfu Zhang, Hisao Ishibuchi:
Enhancing the Convergence Ability of Evolutionary Multi-objective Optimization Algorithms with Momentum. - Duc-Cuong Dang, Andre Opris, Dirk Sudholt:
Illustrating the Efficiency of Popular Evolutionary Multi-Objective Algorithms Using Runtime Analysis. - Benjamin Doerr, Joshua Knowles, Aneta Neumann, Frank Neumann:
A Block-Coordinate Descent EMO Algorithm: Theoretical and Empirical Analysis. - Behrooz Ghasemishabankareh, Xiaodong Li, Melih Ozlen:
User-Preference Based Evolutionary Algorithms for Solving Multi-Objective Nonlinear Minimum Cost Flow Problems. - Cheng Gong, Yang Nan, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang:
Performance of NSGA-III on Multi-objective Combinatorial Optimization Problems Heavily Depends on Its Implementations. - Ishara Hewa Pathiranage, Frank Neumann, Denis Antipov, Aneta Neumann:
Using 3-Objective Evolutionary Algorithms for the Dynamic Chance Constrained Knapsack Problem. - Ahmer Khan, Kalyanmoy Deb:
Innovation Path: Discovering an Ordered Set of Optimized Intermediate Solutions from an Existing to a Desired Solution. - Najwa Kouka, Vincenzo Piuri, Pierangela Samarati:
Tasks Scheduling with Load Balancing in Fog Computing: a Bi-level Multi-Objective Optimization Approach. - Miqing Li, Xiaofeng Han, Xiaochen Chu, Zimin Liang:
Empirical Comparison between MOEAs and Local Search on Multi-Objective Combinatorial Optimisation Problems. - Yanchi Li, Wenyin Gong, Qiong Gu:
Transfer Search Directions Among Decomposed Subtasks for Evolutionary Multitasking in Multiobjective Optimization. - Zhenyu Liang, Tao Jiang, Kebin Sun, Ran Cheng:
GPU-accelerated Evolutionary Multiobjective Optimization Using Tensorized RVEA. - Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang:
Analysis of Real-World Constrained Multi-Objective Problems and Performance Comparison of Multi-Objective Algorithms. - Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang:
Gradient-Guided Local Search for IGD/IGDPlus Subset Selection. - Shakiba Shahbandegan, Emily L. Dolson:
On the robustness of lexicase selection to contradictory objectives. - Shoichiro Tanaka, Gabriela Ochoa, Arnaud Liefooghe, Keiki Takadama, Hiroyuki Sato:
Approximating Pareto Local Optimal Solution Networks. - Deepanshu Yadav, Palaniappan Ramu, Kalyanmoy Deb:
An Updated Performance Metric for Preference-Based Evolutionary Multi-Objective Optimization Algorithms. - Xiankun Yan, Aneta Neumann, Frank Neumann:
Sampling-based Pareto Optimization for Chance-constrained Monotone Submodular Problems. - Rongguang Ye, Longcan Chen, Jinyuan Zhang, Hisao Ishibuchi:
Evolutionary Preference Sampling for Pareto Set Learning. - Fan Yu, Qun Chen, Jinlong Zhou:
Extending Pareto Dominance for Multi-Constraints Satisfaction and Multi-Performance Enhancement in Constrained Multi-Objective Optimization.
Evolutionary Numerical Optimization
- Georgios Andreadis, Tanja Alderliesten, Peter A. N. Bosman:
Fitness-based Linkage Learning and Maximum-Clique Conditional Linkage Modelling for Gray-box Optimization with RV-GOMEA. - Ryoki Hamano, Shota Saito, Masahiro Nomura, Kento Uchida, Shinichi Shirakawa:
CatCMA : Stochastic Optimization for Mixed-Category Problems. - Marcin Michal Komarnicki, Michal Witold Przewozniczek, Renato Tinós, Xiaodong Li:
Overlapping Cooperative Co-Evolution for Overlapping Large-Scale Global Optimization Problems. - David H. Lee, Anishalakshmi V. Palaparthi, Matthew C. Fontaine, Bryon Tjanaka, Stefanos Nikolaidis:
Density Descent for Diversity Optimization. - Hongqiao Lian, Zeyuan Ma, Hongshu Guo, Ting Huang, Yue-Jiao Gong:
RLEMMO: Evolutionary Multimodal Optimization Assisted By Deep Reinforcement Learning. - Daiki Morinaga, Youhei Akimoto:
Sign-Averaging Covariance Matrix Adaptation Evolution Strategy. - Jeremy Porter, Dirk V. Arnold:
Direct Augmented Lagrangian Evolution Strategies. - Ryoji Tanabe:
Benchmarking Parameter Control Methods in Differential Evolution for Mixed-Integer Black-Box Optimization. - Kento Uchida, Ryoki Hamano, Masahiro Nomura, Shota Saito, Shinichi Shirakawa:
CMA-ES for Safe Optimization. - Kento Uchida, Kenta Nishihara, Shinichi Shirakawa:
CMA-ES with Adaptive Reevaluation for Multiplicative Noise.
Genetic Algorithms
- Andrew Festa, Gaurav Dixit, Kagan Tumer:
Reinforcing Inter-Class Dependencies in the Asymmetric Island Model. - Yong-Feng Ge, Hua Wang, Jinli Cao, Yanchun Zhang, Georgios Kambourakis:
Federated Genetic Algorithm: Two-Layer Privacy-Preserving Trajectory Data Publishing. - Yufan Kang, Rongsheng Zhang, Wei Shao, Flora D. Salim, Jeffrey Chan:
Promoting Two-sided Fairness in Dynamic Vehicle Routing Problems. - Gloria Pietropolli, Stefano Nichele, Eric Medvet:
The Role of the Substrate in CA-based Evolutionary Algorithms. - María Riveros, Nicolás Rojas-Morales, Elizabeth Montero, Gabriela Ochoa:
Understanding Search Trajectories in Parameter Tuning. - Furong Ye, Frank Neumann, Jacob de Nobel, Aneta Neumann, Thomas Bäck:
What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms.
General Evolutionary Computation and Hybrids
- Brahim Aboutaib, Andrew M. Sutton:
Mixed Binomial Distributions for Binary Mutation Operators. - Sofya Aksenyuk, Szymon Bujowski, Maciej Komosinski, Konrad Miazga:
Late Bloomers, First Glances, Second Chances: Exploration of the Mechanisms Behind Fitness Diversity. - Darren M. Chitty, James Charles, Alberto Moraglio, Ed Keedwell:
Applying a Quantum Annealer to the Traffic Assignment Problem. - Adam Gaier, James Stoddart, Lorenzo Villaggi, Shyam Sudhakaran:
Generative Design through Quality-Diversity Data Synthesis and Language Models. - Kazuaki Harada, Hitoshi Iba:
Lamarckian Co-design of Soft Robots via Transfer Learning. - Mario Alejandro Hevia Fajardo, Erik Hemberg, Jamal Toutouh, Una-May O'Reilly, Per Kristian Lehre:
A Self-adaptive Coevolutionary Algorithm. - Maciej Komosinski, Agnieszka Mensfelt:
Distance-Targeting Mutation Operator for Evolutionary Design of 3D Structures.
Genetic Programming
- Kirill Antonov, Roman Kalkreuth, Kaifeng Yang, Thomas Bäck, Niki van Stein, Anna V. Kononova:
A Functional Analysis Approach to Symbolic Regression. - Wolfgang Banzhaf, Illya Bakurov:
On the Nature of the Phenotype in Tree Genetic Programming. - Kei Sen Fong, Mehul Motani:
MetaSR: A Meta-Learning Approach to Fitness Formulation for Frequency-Aware Symbolic Regression. - Thomas Helmuth, Jayden Fedoroff, Edward R. Pantridge, Lee Spector:
Facilitating Function Application in Code Building Genetic Programming. - Guilherme Seidyo Imai Aldeia, Fabrício Olivetti de França, William G. La Cava:
Inexact Simplification of Symbolic Regression Expressions with Locality-sensitive Hashing. - Guilherme Seidyo Imai Aldeia, Fabrício Olivetti de França, William G. La Cava:
Minimum variance threshold for epsilon-lexicase selection. - Steven Jorgensen, Giorgia Nadizar, Gloria Pietropolli, Luca Manzoni, Eric Medvet, Una-May O'Reilly, Erik Hemberg:
Large Language Model-based Test Case Generation for GP Agents. - Xiao-Cheng Liao, Yi Mei, Mengjie Zhang:
Learning Traffic Signal Control via Genetic Programming. - Giorgia Nadizar, Eric Medvet, Dennis Wilson:
Searching for a Diversity of Interpretable Graph Control Policies. - Su Nguyen, Dhananjay R. Thiruvady, Yuan Sun, Mengjie Zhang:
Genetic-based Constraint Programming for Resource Constrained Job Scheduling. - Andrew Ni, Lee Spector:
Effective Adaptive Mutation Rates for Program Synthesis. - Etienne Russeil, Fabrício Olivetti de França, Konstantin L. Malanchev, Bogdan Burlacu, Emille E. O. Ishida, Marion Leroux, Clément Michelin, Guillaume Moinard, Emmanuel Gangler:
Multiview Symbolic Regression. - Thalea Schlender, Mafalda Malafaia, Tanja Alderliesten, Peter A. N. Bosman:
Improving the efficiency of GP-GOMEA for higher-arity operators. - Jiahao Wen, Junlan Dong, Jinghui Zhong:
Sign Change Detection based Fitness Evaluation for Automatic Implicit Equation Discovery. - Longfei Felix Yan, Hui Ma, Gang Chen:
Reinforcement Learning-Assisted Genetic Programming Hyper Heuristic Approach to Location-Aware Dynamic Online Application Deployment in Clouds. - Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang:
Bias-Variance Decomposition: An Effective Tool to Improve Generalization of Genetic Programming-based Evolutionary Feature Construction for Regression.
Learning for Evolutionary Computation
- Konstantin Dietrich, Diederick Vermetten, Carola Doerr, Pascal Kerschke:
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization. - Jiyuan Pei, Jialin Liu, Yi Mei:
Learning from Offline and Online Experiences: A Hybrid Adaptive Operator Selection Framework. - Quentin Renau, Emma Hart:
Improving Algorithm-Selectors and Performance-Predictors via Learning Discriminating Training Samples. - Saba Sadeghi Ahouei, Jacob de Nobel, Aneta Neumann, Thomas Bäck, Frank Neumann:
Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem. - Eliad Shem Tov, Achiya Elyasaf:
Deep Neural Crossover: A Multi-Parent Operator That Leverages Gene Correlations. - Jonathan Wurth, Helena Stegherr, Michael Heider, Jörg Hähner:
GRAHF: A Hyper-Heuristic Framework for Evolving Heterogeneous Island Model Topologies. - Tao Xu, Hongyang Chen, Jun He:
Accelerate Evolution Strategy by Proximal Policy Optimization. - Hongjie Xu, Yunzhuang Shen, Yuan Sun, Xiaodong Li:
Machine Learning-Enhanced Ant Colony Optimization for Column Generation.
Neuroevolution
- Manon Flageat, Bryan Lim, Antoine Cully:
Enhancing MAP-Elites with Multiple Parallel Evolution Strategies. - Brandon Morgan, Dean Hougen:
Evolving Loss Functions for Specific Image Augmentation Techniques. - Brandon Morgan, Dean Hougen:
Neural Optimizer Equation, Decay Function, and Learning Rate Schedule Joint Evolution. - Muhammad Umair Nasir, Sam Earle, Julian Togelius, Steven James, Christopher W. Cleghorn:
LLMatic: Neural Architecture Search Via Large Language Models And Quality Diversity Optimization. - Joachim Winther Pedersen, Erwan Plantec, Eleni Nisioti, Milton Montero, Sebastian Risi:
Structurally Flexible Neural Networks: Evolving the Building Blocks for General Agents. - Tran Hai Thanh, Long Doan, Ngoc Hoang Luong, Huynh Thi Thanh Binh:
THNAS-GA: A Genetic Algorithm for Training-free Hardware-aware Neural Architecture Search. - Corinna Triebold, Anil Yaman:
Evolving Generalist Controllers to Handle a Wide Range of Morphological Variations. - An Vo, Ngoc Hoang Luong:
Efficient Multi-Objective Neural Architecture Search via Pareto Dominance-based Novelty Search. - Lishuang Wang, Mengfei Zhao, Enyu Liu, Kebin Sun, Ran Cheng:
Tensorized NeuroEvolution of Augmenting Topologies for GPU Acceleration.
Real World Applications
- Jordan T. Bishop, Jason Jooste, David Howard:
Evolutionary Exploration of Triply Periodic Minimal Surfaces via Quality Diversity. - Mathilde Chen, David Makowski, Alberto Tonda:
Multi-Objective Optimization for Large-scale Allocation of Soybean Crops. - Xiang-Ling Chen, Xiao-Cheng Liao, Feng-Feng Wei, Wei-Neng Chen:
An Order-aware Adaptive Iterative Local Search Metaheuristic for Multi-depot UAV Pickup and Delivery Problem. - Christian Cintrano, Jamal Toutouh, Sergio Nesmachnow:
Optimizing Electric Vehicle Charging Station Placement Integrating Daily Mobility Patterns and Residential Locations. - Victor Hugo Vidigal Corrêa, Thiago Alves de Queiroz, Manuel Iori, André Gustavo dos Santos, Mutsunori Yagiura, Giorgio Zucchi:
Optimizing a Car Patrolling Application by Iterated Local Search. - Felipe Dumont, María Cristina Riff:
2-Step Evolutionary Algorithm for the generation of dungeons with lock door missions using horizontal symmetry. - Mathew Falloon, Hui Ma, Aaron Chen:
Energy-Aware Dynamic Resource Allocation and Container Migration in Cloud Servers: A Co-evolution GPHH Approach. - Fábio Augusto Faria, Luiz Henrique Buris, Luís Augusto Martins Pereira, Fabio Augusto Menocci Cappabianco:
Creating Ensembles of Classifiers through UMDA for Aerial Scene Classification. - Sharlotte Gounder, Frank Neumann, Aneta Neumann:
Evolutionary Diversity Optimisation for Sparse Directed Communication Networks. - Sebastian Gruber, Paul Feichtenschlager, Christoph G. Schuetz:
Using Genetic Algorithms for Privacy-Preserving Optimization of Multi-Objective Assignment Problems in Time-Critical Settings: An Application in Air Traffic Flow Management. - Mujtaba Hassan, Jo Vliegen, Stjepan Picek, Nele Mentens:
A Systematic Exploration of Evolutionary Computation for the Design of Hardware-oriented Non-cryptographic Hash Functions. - Aline Hufschmitt, Patrice Parraud:
Genetic Meta Cipher. - Hannah Janmohamed, Marta Wolinska, Shikha Surana, Thomas Pierrot, Aron Walsh, Antoine Cully:
Multi-Objective Quality-Diversity for Crystal Structure Prediction. - Rachit Kumar, David Zhang, Marylyn DeRiggi Ritchie:
Genetic Algorithm Selection of Interacting Features (GASIF) for Selecting Biological Gene-Gene Interactions. - Atanu Mazumdar, Bhavya Jain, Monisha Mitra, Prodyut Dhar:
Interactive Evolutionary Multiobjective Optimization of Primer Design with Uncertain Objectives. - Eduardo Bouhid Neto, Fábio Augusto Faria, Amanda de Almeida Sales De Oliveira, Álvaro Luiz Fazenda:
A Satellite Band Selection Framework for Amazon Forest Deforestation Detection Task. - Huy Quang Ngo, Mingyu Guo, Hung X. Nguyen:
Optimizing Cyber Response Time on Temporal Active Directory Networks Using Decoys. - Adel Nikfarjam, Ty Stanford, Aneta Neumann, Dorothea Dumuid, Frank Neumann:
Quality Diversity Approaches for Time-Use Optimisation to Improve Health Outcomes. - Akinola Ogunsemi, John A. W. McCall, Alexandru-Ciprian Zavoianu, Lee A. Christie:
Cost and Performance Comparison of Holistic Solution Approaches for Complex Supply Chains on a Novel Linked Problem Benchmark. - Diego Daniel Pedroza-Perez, Jamal Toutouh, Gabriel Luque:
Redesigning road infrastructure to integrate e-scooter micromobility as part of multimodal transportation. - Martina Saletta, Claudio Ferretti:
Exploring the Prompt Space of Large Language Models through Evolutionary Sampling. - Evi Sijben, Jeroen Jansen, Peter A. N. Bosman, Tanja Alderliesten:
Function Class Learning with Genetic Programming: Towards Explainable Meta Learning for Tumor Growth Functionals. - Qurrat Ul Ain, Harith Al-Sahaf, Bing Xue, Mengjie Zhang:
Feature Extraction with Automated Scale Selection in Skin Cancer Image Classification: A Genetic Programming Approach. - Trinh Van Chien, Ngo Tran Anh Thu, Lam Nguyen, Nguyen Binh, Huynh Binh:
On the Performance of User Association in Space-Ground Communications with Integer-Coded Genetic Algorithms. - Aljosa Vodopija, Jordan N. Cork, Bogdan Filipic:
The Lunar Lander Landing Site Selection Benchmark Reexamined: Problem Characterization and Algorithm Performance. - Tongyu Wu, Yuntian Zhang, Changhao Miao, Chen Chen, Shuxin Ding:
Mixed-Variable Correlation-Aware Metaheuristic for Deployment Optimization of 3-D Sensor Networks. - Chixin Xiao, Maoxin He, Dechen Jiang, Yiwei Zhang, Yuxin Tang, Zhenyu Ling:
Differential Evolution Based on Light-Weight-Surrogate for Solving High-Dimensional Energy Management Problem. - Peijie Xu, Andy Song, Ke Wang:
Genetic Programming Empowered Feature Construction towards Energy Efficient BVI Wearables. - Yingfang Yuan, Wenjun Wang, Xin Li, Kefan Chen, Yonghan Zhang, Wei Pang:
Evolving Molecular Graph Neural Networks with Hierarchical Evaluation Strategy.
Search-Based Software Engineering
- Michael Auer, Dominik Diner, Gordon Fraser:
Search-based Crash Reproduction for Android Apps. - Deyun Lyu, Zhenya Zhang, Paolo Arcaini, Fuyuki Ishikawa, Thomas Laurent, Jianjun Zhao:
Search-Based Repair of DNN Controllers of AI-Enabled Cyber-Physical Systems Guided by System-Level Specifications. - Francisco Zanartu, Christoph Treude, Markus Wagner:
Socialz: Multi-Feature Social Fuzz Testing.
Swarm Intelligence
- Mehmet Anil Akbay, Christian Blum, Michella Saliba:
The Electric Vehicle Problem with Road Junctions and Road Types: An Ant Colony Optimization Approach. - Aseel Ismael Ali, Edward C. Keedwell, Ayah Helal:
A Differential Pheromone Grouping Ant Colony Optimization Algorithm for the 1-D Bin Packing Problem. - Ting Dong, Haoxin Wang, Wenbo Ding, Libao Shi:
A Self-adaptive Rotationally Invariant Particle Swarm Optimization for Global Optimization. - Kordel France, Anirban Paul, Ivneet Banga, Shalini Prasad:
Emergent Behavior in Evolutionary Swarms for Machine Olfaction. - Matthias Kergaßner, Oliver Keszöcze, Rolf Wanka:
Markov Chain-based Optimization Time Analysis of Bivalent Ant Colony Optimization for Sorting and LeadingOnes. - Zeyuan Ma, Jiacheng Chen, Hongshu Guo, Yining Ma, Yue-Jiao Gong:
Auto-configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learning. - Xin-Yu Wang, Qi-Te Yang, Yi Jiang, Kay Chen Tan, Jun Zhang, Zhi-Hui Zhan:
Fine-Grain Knowledge Transfer-based Multitask Particle Swarm Optimization with Dual Clustering-based Task Generation for High-Dimensional Feature Selection. - Yong Zhang, Ke-Jing Du, Yi Jiang, Li-Min Wang, Hua Wang, Zhi-Hui Zhan:
Adaptive Aggregative Multitask Competitive Particle Swarm Optimization with Bi-Directional Asymmetric Flip Strategy for High-Dimensional Feature Selection.
Theory
- Denis Antipov, Benjamin Doerr, Alexandra Ivanova:
Already Moderate Population Sizes Provably Yield Strong Robustness to Noise. - Jakob Baumann, Ignaz Rutter, Dirk Sudholt:
Evolutionary Computation Meets Graph Drawing: Runtime Analysis for Crossing Minimisation on Layered Graph Drawings. - Alistair Benford, Per Kristian Lehre:
Runtime Analysis of Coevolutionary Algorithms on a Class of Symmetric Zero-Sum Games. - Duc-Cuong Dang, Per Kristian Lehre:
The SLO Hierarchy of pseudo-Boolean Functions and Runtime of Evolutionary Algorithms. - Paul Fischer, John Alasdair Warwicker, Carsten Witt:
A Runtime Analysis of Bias-invariant Neuroevolution and Dynamic Fitness Evaluation. - Jonathan Gadea Harder, Timo Kötzing, Xiaoyue Li, Aishwarya Radhakrishnan, Janosch Ruff:
Run Time Bounds for Integer-Valued OneMax Functions. - Martin S. Krejca, Carsten Witt:
A Flexible Evolutionary Algorithm with Dynamic Mutation Rate Archive. - Johannes Lengler, Leon Schiller, Oliver Sieberling:
Plus Strategies are Exponentially Slower for Planted Optima of Random Height. - Andre Opris, Duc-Cuong Dang, Frank Neumann, Dirk Sudholt:
Runtime Analyses of NSGA-III on Many-Objective Problems. - Andre Opris, Johannes Lengler, Dirk Sudholt:
A Tight O(4k/pc) Runtime Bound for a (μ+1)GA on Jumpk for Realistic Crossover Probabilities. - Marcus Schmidbauer, Andre Opris, Jakob Bossek, Frank Neumann, Dirk Sudholt:
Guiding Quality Diversity on Monotone Submodular Functions: Customising the Feature Space by Adding Boolean Conjunctions.
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