University of Adelaide demonstrates leadership in Evolutionary Computation at GECCO 2024
15 full research papers accepted at the Genetic and Evolutionary Computation Conference 2024.
Xiankun Yan, Thilina Chathuranga Pathirage Don, Dr Hirad Assimi, Professor Frank Neumann, Dr Marcus Martens, Saba Sadeghi Ahouei, Kokila Perera, Ishara Hewa Pathiranage, Dr Denis Antipov, Adjunct Associate Professor Markus Wagner.
Optimisation and Logistics researchers from the School of Computer and Mathematical Sciences and their national and international collaborators have had 15 papers accepted for the prestigious GECCO 2024 conference, demonstrating leadership within this field.
The GECCO conference, commenced on Sunday 14 July to 18 July, in Melbourne and is a platform to showcase world-class research to peers and industry.
It is the main annual conference of the Special Interest Group on Genetic and Evolutionary Computation (SIGEVO), which is a Special Interest Group (SIG) of the Association for Computing Machinery (ACM).
The list of papers that were accepted from researchers at the School includes:
| Track | Title | Authors |
|---|---|---|
| ECOM | Effective 2- and 3-Objective MOEA/D Approaches for the Chance Constrained Knapsack Problem | Ishara Hewa Pathiranage (The University of Adelaide), Frank Neumann (The University of Adelaide), Denis Antipov (The University of Adelaide), Aneta Neumann (The University of Adelaide) |
| ECOM | Multi-objective Evolutionary Algorithm with Sliding Window Selection for the Dynamic Chance-Constrained Knapsack Problem | Kokila Perera (The University of Adelaide), Aneta Neumann (The University of Adelaide) |
| ECOM | The Chance Constrained Travelling Thief Problem: Problem Formulations and Algorithms | Thilina Chathuranga Pathirage Don (University of Adelaide), Aneta Neumann (University of Adelaide), Frank Neumann (University of Adelaide) |
| EMO | A Block-Coordinate Descent EMO Algorithm: Theoretical and Empirical Analysis | Benjamin Doerr (École Polytechnique), Joshua Knowles (Schlumberger), Aneta Neumann (The University of Adelaide), Frank Neumann (The University of Adelaide) |
| EMO | Using 3-Objective Evolutionary Algorithms for the Dynamic Chance Constrained Knapsack Problem | Ishara Hewa Pathiranage (The University of Adelaide), Frank Neumann (The University of Adelaide), Denis Antipov (The University of Adelaide), Aneta Neumann (The University of Adelaide) |
| EMO | A Detailed Experimental Analysis of Evolutionary Diversity Optimization for OneMinMax | Denis Antipov (The University of Adelaide), Aneta Neumann (The University of Adelaide), Frank Neumann (The University of Adelaide) |
| EMO | Sampling-based Pareto Optimization for Chance-constrained Monotone Submodular Problems | Xiankun Yan (The University of Adelaide), Aneta Neumann (The University of Adelaide), Frank Neumann (The University of Adelaide) |
| GA | What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms | Furong Ye (Chinese Academy of Sciences), Frank Neumann (The University of Adelaide), Jacob de Nobel (Leiden University), Aneta Neumann (The University of Adelaide), Thomas Bäck (Leiden University) |
| L4EC | Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem | Saba Sadeghi Ahouei (The University of Adelaide), Jacob de Nobel (Leiden University), Aneta Neumann (The University of Adelaide), Frank Neumann (The University of Adelaide), Thomas Bäck (Leiden University) |
| RWA | Optimizing Cyber Response Time on Temporal Active Directory Networks Using Decoys | Huy Quang Ngo (The University of Adelaide), Mingyu Guo (The University of Adelaide), Hung Nguyen (The University of Adelaide) |
| RWA | Evolutionary Diversity Optimisation for Sparse Directed Communication Networks | Sharlotte Gounder (The University of Adelaide), Frank Neumann (The University of Adelaide), Aneta Neumann (The University of Adelaide) |
| RWA | Quality Diversity Approaches for Time-Use Optimisation to Improve Health Outcomes | Adel Nikfarjam (The University of Adelaide), Ty Stanford (The University of South Australia), Aneta Neumann (The University of Adelaide), Dorothea Dumuid (The University of South Australia), Frank Neumann (The University of Adelaide) |
| THEORY | Already Moderate Population Sizes Provably Yield Strong Robustness to Noise | Denis Antipov (The University of Adelaide), Benjamin Doerr (École Polytechnique), Alexandra Ivanova (HSE University, Skoltech) |
| THEORY | Runtime Analyses of NSGA-III on Many-Objective Problems | Andre Opris (University of Passau), Duc-Cuong Dang (University of Passau), Frank Neumann (University of Adelaide), Dirk Sudholt (University of Passau) |
| THEORY | Guiding Quality Diversity on Monotone Submodular Functions: Customising the Feature Space by Adding Boolean Conjunctions | Marcus Schmidbauer (University of Passau), Andre Opris (University of Passau), Jakob Bossek (University of Paderborn), Frank Neumann (University of Adelaide), Dirk Sudholt (University of Passau) |
About GECCO
The Genetic and Evolutionary Computation Conference (GECCO) is the leading international conference on genetic and evolutionary computation and presents the latest high-quality results in this research area since 1999. Topics include: genetic algorithms, genetic programming, swarm intelligence, complex systems, evolutionary combinatorial optimization and metaheuristics, evolutionary machine learning, learning for evolutionary computation, evolutionary multiobjective optimization, evolutionary numerical optimization, neuroevolution, real world applications, search-based software engineering, theory, benchmarking, reproducibility, hybrids and more.