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ORCIDFrank Neumann 0001
Person information
- affiliation: University of Adelaide, Australia
- affiliation: Max Planck Institute for Informatics, Saarbrücken, Germany
Other persons with the same name
- Frank Neumann 0002 — Technical University of Berlin, Germany
- Frank Neumann 0003 — Universität Hannover, Theoretische Chemie, Germany
- Frank Neumann 0004 — HTW Berlin - University of Applied Sciences, Germany
- Frank Neumann 0005 — University of Leicester, School of Mathematics and Actuarial Science, UK
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2020 – today
- 2024
[j68]Adel Nikfarjam
, Aneta Neumann, Frank Neumann:
On the Use of Quality Diversity Algorithms for the Travelling Thief Problem. ACM Trans. Evol. Learn. Optim. 4(2): 12 (2024)- [c249]Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung X. Nguyen:
Limited Query Graph Connectivity Test. AAAI 2024: 20718-20725 - [c248]Zahra Ghasemi, Mehdi Neshat, Chris Aldrich, John Karageorgos, Max Zanin, Frank Neumann, Lei Chen:
Enhanced Genetic Programming Models with Multiple Equations for Accurate Semi-Autogenous Grinding Mill Throughput Prediction. CEC 2024: 1-9 - [c247]Frank Neumann, Aneta Neumann, Hemant Kumar Singh:
Evolutionary computation for stochastic problems. GECCO Companion 2024: 1352-1368 - [c246]Saba Sadeghi Ahouei, Jacob de Nobel, Aneta Neumann, Thomas Bäck, Frank Neumann:
Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem. GECCO 2024 - [c245]Denis Antipov, Aneta Neumann, Frank Neumann:
A Detailed Experimental Analysis of Evolutionary Diversity Optimization for OneMinMax. GECCO 2024 - [c244]Benjamin Doerr, Joshua D. Knowles, Aneta Neumann, Frank Neumann:
A Block-Coordinate Descent EMO Algorithm: Theoretical and Empirical Analysis. GECCO 2024 - [c243]Thilina Pathirage Don, Aneta Neumann, Frank Neumann:
The Chance Constrained Travelling Thief Problem: Problem Formulations and Algorithms. GECCO 2024 - [c242]Sharlotte Gounder, Frank Neumann, Aneta Neumann:
Evolutionary Diversity Optimisation for Sparse Directed Communication Networks. GECCO 2024 - [c241]Adel Nikfarjam, Ty Stanford, Aneta Neumann, Dorothea Dumuid, Frank Neumann:
Quality Diversity Approaches for Time-Use Optimisation to Improve Health Outcomes. GECCO 2024 - [c240]Andre Opris, Duc-Cuong Dang, Frank Neumann, Dirk Sudholt:
Runtime Analyses of NSGA-III on Many-Objective Problems. GECCO 2024 - [c239]Ishara Hewa Pathiranage, Frank Neumann, Denis Antipov, Aneta Neumann:
Effective 2- and 3-Objective MOEA/D Approaches for the Chance Constrained Knapsack Problem. GECCO 2024 - [c238]Ishara Hewa Pathiranage, Frank Neumann, Denis Antipov, Aneta Neumann:
Using 3-Objective Evolutionary Algorithms for the Dynamic Chance Constrained Knapsack Problem. GECCO 2024 - [c237]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. GECCO 2024 - [c236]Xiankun Yan, Aneta Neumann, Frank Neumann:
Sampling-based Pareto Optimization for Chance-constrained Monotone Submodular Problems. GECCO 2024 - [c235]Furong Ye, Frank Neumann, Jacob de Nobel, Aneta Neumann, Thomas Bäck:
What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms. GECCO 2024 - [c234]Denis Antipov, Aneta Neumann, Frank Neumann, Andrew M. Sutton:
Runtime Analysis of Evolutionary Diversity Optimization on a Tri-Objective Version of the (LeadingOnes, TrailingZeros) Problem. PPSN (3) 2024: 19-35 - [c233]Xiankun Yan, Aneta Neumann, Frank Neumann:
Sliding Window Bi-objective Evolutionary Algorithms for Optimizing Chance-Constrained Monotone Submodular Functions. PPSN (1) 2024: 20-35 - [c232]Frank Neumann, Carsten Witt:
Sliding Window 3-Objective Pareto Optimization for Problems with Chance Constraints. PPSN (3) 2024: 36-52 - [c231]Kokila Kasuni Perera, Frank Neumann, Aneta Neumann:
Multi-objective Evolutionary Approaches for the Knapsack Problem with Stochastic Profits. PPSN (1) 2024: 116-132 - [c230]Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann:
Evolutionary Multi-objective Diversity Optimization. PPSN (4) 2024: 117-134 - [c229]Jonathan Gadea Harder, Aneta Neumann, Frank Neumann:
Analysis of Evolutionary Diversity Optimisation for the Maximum Matching Problem. PPSN (3) 2024: 149-165 - [c228]Frank Neumann, Günter Rudolph:
Archive-Based Single-Objective Evolutionary Algorithms for Submodular Optimization. PPSN (3) 2024: 166-180 - [c227]Denis Antipov, Aneta Neumann, Frank Neumann:
Local Optima in Diversity Optimization: Non-trivial Offspring Population is Essential. PPSN (3) 2024: 181-196 - [i145]Zahra Ghasemi, Mehdi Neshat, Chris Aldrich, John Karageorgos, Max Zanin, Frank Neumann, Lei Chen:
Enhanced Genetic Programming Models with Multiple Equations for Accurate Semi-Autogenous Grinding Mill Throughput Prediction. CoRR abs/2401.05382 (2024) - [i144]Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann:
Evolutionary Multi-Objective Diversity Optimization. CoRR abs/2401.07454 (2024) - [i143]Benjamin Doerr, Joshua D. Knowles, Aneta Neumann, Frank Neumann:
A Block-Coordinate Descent EMO Algorithm: Theoretical and Empirical Analysis. CoRR abs/2404.03838 (2024) - [i142]Ishara Hewa Pathiranage, Frank Neumann, Denis Antipov, Aneta Neumann:
Using 3-Objective Evolutionary Algorithms for the Dynamic Chance Constrained Knapsack Problem. CoRR abs/2404.06014 (2024) - [i141]Andre Opris, Duc-Cuong Dang, Frank Neumann, Dirk Sudholt:
Runtime Analyses of NSGA-III on Many-Objective Problems. CoRR abs/2404.11433 (2024) - [i140]Denis Antipov, Aneta Neumann, Frank Neumann, Andrew M. Sutton:
Runtime Analysis of Evolutionary Diversity Optimization on the Multi-objective (LeadingOnes, TrailingZeros) Problem. CoRR abs/2404.11496 (2024) - [i139]Jonathan Gadea Harder, Aneta Neumann, Frank Neumann:
Analysis of Evolutionary Diversity Optimisation for the Maximum Matching Problem. CoRR abs/2404.11784 (2024) - [i138]Xiankun Yan, Aneta Neumann, Frank Neumann:
Sampling-based Pareto Optimization for Chance-constrained Monotone Submodular Problems. CoRR abs/2404.11907 (2024) - [i137]Saba Sadeghi Ahouei, Jacob de Nobel, Aneta Neumann, Thomas Bäck, Frank Neumann:
Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem. CoRR abs/2405.18772 (2024) - [i136]Frank Neumann, Carsten Witt:
Sliding Window 3-Objective Pareto Optimization for Problems with Chance Constraints. CoRR abs/2406.04899 (2024) - [i135]Frank Neumann, Günter Rudolph:
Archive-based Single-Objective Evolutionary Algorithms for Submodular Optimization. CoRR abs/2406.13414 (2024) - [i134]Denis Antipov, Aneta Neumann, Frank Neumann:
Local Optima in Diversity Optimization: Non-trivial Offspring Population is Essential. CoRR abs/2407.08963 (2024) - [i133]Xiankun Yan, Aneta Neumann, Frank Neumann:
Sliding Window Bi-Objective Evolutionary Algorithms for Optimizing Chance-Constrained Monotone Submodular Functions. CoRR abs/2407.09731 (2024) - [i132]Maria Laura Santoni, Elena Raponi, Aneta Neumann, Frank Neumann, Mike Preuss, Carola Doerr:
Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization. CoRR abs/2408.16393 (2024) - [i131]Jack Kearney, Frank Neumann, Andrew M. Sutton:
Fixed-Parameter Tractability of the (1+1) Evolutionary Algorithm on Random Planted Vertex Covers. CoRR abs/2409.10144 (2024) - [i130]Duc-Cuong Dang, Aneta Neumann, Frank Neumann, Andre Opris, Dirk Sudholt:
Theoretical Analysis of Quality Diversity Algorithms for a Classical Path Planning Problem. CoRR abs/2412.11446 (2024) - 2023
- [c226]Mingyu Guo, Max Ward, Aneta Neumann, Frank Neumann, Hung Nguyen:
Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs. AAAI 2023: 5649-5656 - [c225]Gabor Zoltai, Yue Xie, Frank Neumann:
A Study of Fitness Gains in Evolving Finite State Machines. AI (2) 2023: 479-490 - [c224]Frank Neumann, Aneta Neumann, Chao Qian, Anh Viet Do, Jacob de Nobel, Diederick Vermetten, Saba Sadeghi Ahouei, Furong Ye, Hao Wang, Thomas Bäck:
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. CEC 2023: 1-9 - [c223]Michael Stimson, William Reid, Aneta Neumann, Simon Ratcliffe, Frank Neumann:
Improving Confidence in Evolutionary Mine Scheduling via Uncertainty Discounting. CEC 2023: 1-10 - [c222]Frank Neumann, Carsten Witt:
Fast Pareto Optimization Using Sliding Window Selection. ECAI 2023: 1771-1778 - [c221]Xiankun Yan, Anh Viet Do, Feng Shi, Xiaoyu Qin, Frank Neumann:
Optimizing Chance-Constrained Submodular Problems with Variable Uncertainties. ECAI 2023: 2826-2833 - [c220]Denis Antipov, Aneta Neumann, Frank Neumann:
Rigorous Runtime Analysis of Diversity Optimization with GSEMO on OneMinMax. FOGA 2023: 3-14 - [c219]Jack Kearney, Frank Neumann, Andrew M. Sutton:
Fixed-Parameter Tractability of the (1 + 1) Evolutionary Algorithm on Random Planted Vertex Covers. FOGA 2023: 96-104 - [c218]Jakob Bossek, Aneta Neumann, Frank Neumann:
On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem. GECCO 2023: 248-256 - [c217]Frank Neumann, Carsten Witt:
3-Objective Pareto Optimization for Problems with Chance Constraints. GECCO 2023: 731-739 - [c216]Adel Nikfarjam, Ralf Rothenberger, Frank Neumann, Tobias Friedrich:
Evolutionary Diversity Optimisation in Constructing Satisfying Assignments. GECCO 2023: 938-945 - [c215]Diksha Goel, Aneta Neumann, Frank Neumann, Hung Nguyen, Mingyu Guo:
Evolving Reinforcement Learning Environment to Minimize Learner's Achievable Reward: An Application on Hardening Active Directory Systems. GECCO 2023: 1348-1356 - [c214]Aneta Neumann, Sharlotte Gounder, Xiankun Yan, Gregory Sherman, Benjamin Campbell, Mingyu Guo, Frank Neumann:
Diversity Optimization for the Detection and Concealment of Spatially Defined Communication Networks. GECCO 2023: 1436-1444 - [c213]Frank Neumann, Aneta Neumann, Hemant K. Singh:
Evolutionary computation for stochastic problems. GECCO Companion 2023: 1463-1476 - [c212]Samuel Baguley, Tobias Friedrich, Aneta Neumann, Frank Neumann, Marcus Pappik, Ziena Zeif:
Fixed Parameter Multi-Objective Evolutionary Algorithms for the W-Separator Problem. GECCO 2023: 1537-1545 - [c211]Tobias Friedrich, Timo Kötzing, Aneta Neumann, Frank Neumann, Aishwarya Radhakrishnan:
Analysis of (1+1) EA on LeadingOnes with Constraints. GECCO 2023: 1584-1592 - [c210]Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann:
Diverse Approximations for Monotone Submodular Maximization Problems with a Matroid Constraint. IJCAI 2023: 5558-5566 - [c209]Anh Viet Do, Aneta Neumann, Frank Neumann, Andrew M. Sutton:
Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems. NeurIPS 2023 - [i129]Frank Neumann, Aneta Neumann, Chao Qian, Anh Viet Do, Jacob de Nobel, Diederick Vermetten, Saba Sadeghi Ahouei, Furong Ye, Hao Wang, Thomas Bäck:
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. CoRR abs/2302.01464 (2023) - [i128]Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen:
Limited Query Graph Connectivity Test. CoRR abs/2302.13036 (2023) - [i127]Kokila Perera, Aneta Neumann, Frank Neumann:
Evolutionary Multi-Objective Algorithms for the Knapsack Problems with Stochastic Profits. CoRR abs/2303.01695 (2023) - [i126]Furong Ye, Frank Neumann, Jacob de Nobel, Aneta Neumann, Thomas Bäck:
What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms. CoRR abs/2303.04611 (2023) - [i125]Diksha Goel, Aneta Neumann, Frank Neumann, Hung Nguyen, Mingyu Guo:
Evolving Reinforcement Learning Environment to Minimize Learner's Achievable Reward: An Application on Hardening Active Directory Systems. CoRR abs/2304.03998 (2023) - [i124]Frank Neumann, Carsten Witt:
3-Objective Pareto Optimization for Problems with Chance Constraints. CoRR abs/2304.08774 (2023) - [i123]Frank Neumann, Carsten Witt:
Fast Pareto Optimization Using Sliding Window Selection. CoRR abs/2305.07178 (2023) - [i122]Adel Nikfarjam, Ralf Rothenberger, Frank Neumann, Tobias Friedrich:
Evolutionary Diversity Optimisation in Constructing Satisfying Assignments. CoRR abs/2305.11457 (2023) - [i121]Michael Stimson, William Reid, Aneta Neumann, Simon Ratcliffe, Frank Neumann:
Improving Confidence in Evolutionary Mine Scheduling via Uncertainty Discounting. CoRR abs/2305.17957 (2023) - [i120]Tobias Friedrich, Timo Kötzing, Aneta Neumann, Frank Neumann, Aishwarya Radhakrishnan:
Analysis of the (1+1) EA on LeadingOnes with Constraints. CoRR abs/2305.18267 (2023) - [i119]Jakob Bossek, Aneta Neumann, Frank Neumann:
On the Impact of Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem. CoRR abs/2305.18955 (2023) - [i118]Anh Viet Do, Aneta Neumann, Frank Neumann, Andrew M. Sutton:
Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems. CoRR abs/2306.03409 (2023) - [i117]Denis Antipov, Aneta Neumann, Frank Neumann:
Rigorous Runtime Analysis of Diversity Optimization with GSEMO on OneMinMax. CoRR abs/2307.07248 (2023) - [i116]Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann:
Diverse Approximations for Monotone Submodular Maximization Problems with a Matroid Constraint. CoRR abs/2307.07567 (2023) - [i115]Xiankun Yan, Anh Viet Do, Feng Shi, Xiaoyu Qin, Frank Neumann:
Optimizing Chance-Constrained Submodular Problems with Variable Uncertainties. CoRR abs/2309.14359 (2023) - [i114]Gabor Zoltai, Yue Xie, Frank Neumann:
A Study of Fitness Gains in Evolving Finite State Machines. CoRR abs/2310.13203 (2023) - [i113]Zahra Ghasemi, Mehdi Neshat, Chris Aldrich, John Karageorgos, Max Zanin, Frank Neumann, Lei Chen:
A Hybrid Intelligent Framework for Maximising SAG Mill Throughput: An Integration of Expert Knowledge, Machine Learning and Evolutionary Algorithms for Parameter Optimisation. CoRR abs/2312.10992 (2023) - 2022
- [j67]Vahid Roostapour, Aneta Neumann, Frank Neumann, Tobias Friedrich:
Pareto optimization for subset selection with dynamic cost constraints. Artif. Intell. 302: 103597 (2022) - [j66]Johannes Lengler, Frank Neumann:
Editorial. Algorithmica 84(6): 1571-1572 (2022) - [j65]Vahid Roostapour, Aneta Neumann, Frank Neumann:
Single- and multi-objective evolutionary algorithms for the knapsack problem with dynamically changing constraints. Theor. Comput. Sci. 924: 129-147 (2022) - [j64]Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann:
Analysis of Evolutionary Diversity Optimization for Permutation Problems. ACM Trans. Evol. Learn. Optim. 2(3): 11:1-11:27 (2022) - [c208]Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen:
Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs. AAAI 2022: 9360-9367 - [c207]Hirad Assimi, Frank Neumann, Markus Wagner, Xiaodong Li:
Novelty-Driven Binary Particle Swarm Optimisation for Truss Optimisation Problems. EvoCOP 2022: 111-126 - [c206]Jakob Bossek, Frank Neumann:
Exploring the feature space of TSP instances using quality diversity. GECCO 2022: 186-194 - [c205]Adel Nikfarjam, Aneta Neumann, Frank Neumann:
On the use of quality diversity algorithms for the traveling thief problem. GECCO 2022: 260-268 - [c204]Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann:
Niching-based evolutionary diversity optimization for the traveling salesperson problem. GECCO 2022: 684-693 - [c203]Adel Nikfarjam, Aneta Neumann, Frank Neumann:
Evolutionary diversity optimisation for the traveling thief problem. GECCO 2022: 749-756 - [c202]Yue Xie, Aneta Neumann, Frank Neumann:
An optimization strategy for the complex large-scale stockpile blending problem. GECCO Companion 2022: 770-773 - [c201]Jakob Bossek, Aneta Neumann, Frank Neumann:
Evolutionary diversity optimization for combinatorial optimization: tutorial at GECCO'22, Boston, USA. GECCO Companion 2022: 824-842 - [c200]Aneta Neumann, Denis Antipov, Frank Neumann:
Coevolutionary Pareto diversity optimization. GECCO 2022: 832-839 - [c199]Diksha Goel, Max Hector Ward-Graham, Aneta Neumann, Frank Neumann, Hung Nguyen, Mingyu Guo:
Defending active directory by combining neural network based dynamic program and evolutionary diversity optimisation. GECCO 2022: 1191-1199 - [c198]Frank Neumann, Dirk Sudholt, Carsten Witt:
The compact genetic algorithm struggles on Cliff functions. GECCO 2022: 1426-1433 - [c197]Aneta Neumann, Frank Neumann, Chao Qian:
Evolutionary submodular optimisation: tutorial. GECCO Companion 2022: 1427-1449 - [c196]Frank Neumann, Carsten Witt:
Runtime Analysis of Single- and Multi-Objective Evolutionary Algorithms for Chance Constrained Optimization Problems with Normally Distributed Random Variables. IJCAI 2022: 4800-4806 - [c195]Adel Nikfarjam, Aneta Neumann, Jakob Bossek, Frank Neumann:
Co-evolutionary Diversity Optimisation for the Traveling Thief Problem. PPSN (1) 2022: 237-249 - [c194]Adel Nikfarjam, Amirhossein Moosavi, Aneta Neumann, Frank Neumann:
Computing High-Quality Solutions for the Patient Admission Scheduling Problem Using Evolutionary Diversity Optimisation. PPSN (1) 2022: 250-264 - [c193]Aneta Neumann, Yue Xie, Frank Neumann:
Evolutionary Algorithms for Limiting the Effect of Uncertainty for the Knapsack Problem with Stochastic Profits. PPSN (1) 2022: 294-307 - [c192]Yue Xie, Aneta Neumann, Ty Stanford, Charlotte Lund Rasmussen, Dorothea Dumuid, Frank Neumann:
Evolutionary Time-Use Optimization for Improving Children's Health Outcomes. PPSN (2) 2022: 323-337 - [c191]Adel Nikfarjam, Anh Viet Do, Frank Neumann:
Analysis of Quality Diversity Algorithms for the Knapsack Problem. PPSN (2) 2022: 413-427 - [c190]Feng Shi, Xiankun Yan, Frank Neumann:
Runtime Analysis of Simple Evolutionary Algorithms for the Chance-Constrained Makespan Scheduling Problem. PPSN (2) 2022: 526-541 - [c189]Frank Neumann, Carsten Witt:
Runtime Analysis of the (1+1) EA on Weighted Sums of Transformed Linear Functions. PPSN (2) 2022: 542-554 - [c188]Tobias Friedrich, Timo Kötzing, Frank Neumann, Aishwarya Radhakrishnan:
Theoretical Study of Optimizing Rugged Landscapes with the cGA. PPSN (2) 2022: 586-599 - [c187]Hirad Assimi, Ben Koch, Chris Garcia, Markus Wagner, Frank Neumann:
Run-of-mine stockyard recovery scheduling and optimisation for multiple reclaimers. SAC 2022: 1074-1083 - [i112]Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann:
Niching-based Evolutionary Diversity Optimization for the Traveling Salesperson Problem. CoRR abs/2201.10316 (2022) - [i111]Jakob Bossek, Frank Neumann:
Exploring the Feature Space of TSP Instances Using Quality Diversity. CoRR abs/2202.02077 (2022) - [i110]Adel Nikfarjam, Aneta Neumann, Frank Neumann:
Evolutionary Diversity Optimisation for The Traveling Thief Problem. CoRR abs/2204.02709 (2022) - [i109]Diksha Goel, Max Ward, Aneta Neumann, Frank Neumann, Hung Nguyen, Mingyu Guo:
Defending Active Directory by Combining Neural Network based Dynamic Program and Evolutionary Diversity Optimisation. CoRR abs/2204.03397 (2022) - [i108]Frank Neumann, Dirk Sudholt, Carsten Witt:
The Compact Genetic Algorithm Struggles on Cliff Functions. CoRR abs/2204.04904 (2022) - [i107]Aneta Neumann, Denis Antipov, Frank Neumann:
Coevolutionary Pareto Diversity Optimization. CoRR abs/2204.05457 (2022) - [i106]Aneta Neumann, Yue Xie, Frank Neumann:
Evolutionary Algorithms for Limiting the Effect of Uncertainty for the Knapsack Problem with Stochastic Profits. CoRR abs/2204.05597 (2022) - [i105]Yue Xie, Aneta Neumann, Ty Stanford, Charlotte Lund Rasmussen, Dorothea Dumuid, Frank Neumann:
Evolutionary Time-Use Optimization for Improving Children's Health Outcomes. CoRR abs/2206.11505 (2022) - [i104]Adel Nikfarjam, Aneta Neumann, Jakob Bossek, Frank Neumann:
Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem. CoRR abs/2207.14036 (2022) - [i103]Adel Nikfarjam, Anh Viet Do, Frank Neumann:
Analysis of Quality Diversity Algorithms for the Knapsack Problem. CoRR abs/2207.14037 (2022) - [i102]Adel Nikfarjam, Amirhossein Moosavi, Aneta Neumann, Frank Neumann:
Computing High-Quality Solutions for the Patient Admission Scheduling Problem using Evolutionary Diversity Optimisation. CoRR abs/2207.14112 (2022) - [i101]Frank Neumann, Carsten Witt<