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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
- 2023
[i120]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)- [i119]Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen:
Limited Query Graph Connectivity Test. CoRR abs/2302.13036 (2023) - [i118]Kokila Perera, Aneta Neumann, Frank Neumann:
Evolutionary Multi-Objective Algorithms for the Knapsack Problems with Stochastic Profits. CoRR abs/2303.01695 (2023) - [i117]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) - [i116]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) - [i115]Frank Neumann, Carsten Witt:
3-Objective Pareto Optimization for Problems with Chance Constraints. CoRR abs/2304.08774 (2023) - [i114]Frank Neumann, Carsten Witt:
Fast Pareto Optimization Using Sliding Window Selection. CoRR abs/2305.07178 (2023) - [i113]Adel Nikfarjam, Ralf Rothenberger, Frank Neumann, Tobias Friedrich:
Evolutionary Diversity Optimisation in Constructing Satisfying Assignments. CoRR abs/2305.11457 (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:
Runtime Analysis of the (1+1) EA on Weighted Sums of Transformed Linear Functions. CoRR abs/2208.05670 (2022) - [i100]Tobias Friedrich, Timo Kötzing, Frank Neumann, Aishwarya Radhakrishnan:
Theoretical Study of Optimizing Rugged Landscapes with the cGA. CoRR abs/2211.13801 (2022) - [i99]Mingyu Guo, Max Ward, Aneta Neumann, Frank Neumann, Hung Nguyen:
Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs. CoRR abs/2212.04326 (2022) - [i98]Feng Shi, Xiankun Yan, Frank Neumann:
Runtime Performance of Evolutionary Algorithms for the Chance-constrained Makespan Scheduling Problem. CoRR abs/2212.11478 (2022) - 2021
- [j63]Feng Shi, Frank Neumann, Jianxin Wang:
Runtime Performances of Randomized Search Heuristics for the Dynamic Weighted Vertex Cover Problem. Algorithmica 83(4): 906-939 (2021) - [j62]Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt:
Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. Algorithmica 83(10): 3148-3179 (2021) - [j61]Frank Neumann, Mojgan Pourhassan, Carsten Witt:
Improved Runtime Results for Simple Randomised Search Heuristics on Linear Functions with a Uniform Constraint. Algorithmica 83(10): 3209-3237 (2021) - [j60]Wanru Gao, Samadhi Nallaperuma, Frank Neumann:
Feature-Based Diversity Optimization for Problem Instance Classification. Evol. Comput. 29(1): 107-128 (2021) - [j59]Derek Weber, Frank Neumann:
Amplifying influence through coordinated behaviour in social networks. Soc. Netw. Anal. Min. 11(1): 111 (2021) - [j58]Feng Shi, Frank Neumann, Jianxin Wang:
Time complexity analysis of evolutionary algorithms for 2-hop (1, 2)-minimum spanning tree problem. Theor. Comput. Sci. 893: 159-175 (2021) - [j57]Benjamin Doerr, Frank Neumann:
A Survey on Recent Progress in the Theory of Evolutionary Algorithms for Discrete Optimization. ACM Trans. Evol. Learn. Optim. 1(4): 16:1-16:43 (2021) - [c186]Anh Viet Do, Frank Neumann:
Pareto Optimization for Subset Selection with Dynamic Partition Matroid Constraints. AAAI 2021: 12284-12292 - [c185]Yue Xie, Aneta Neumann, Frank Neumann:
Heuristic Strategies for Solving Complex Interacting Large-Scale Stockpile Blending Problems. CEC 2021: 1288-1295 - [c184]Adel Nikfarjam, Jakob Bossek, Aneta Neumann, Frank Neumann:
Computing diverse sets of high quality TSP tours by EAX-based evolutionary diversity optimisation. FOGA 2021: 9:1-9:11 - [c183]Hirad Assimi, Frank Neumann, Markus Wagner, Xiaodong Li:
Novelty particle swarm optimisation for truss optimisation problems. GECCO Companion 2021: 67-68 - [c182]Jakob Bossek, Frank Neumann:
Evolutionary diversity optimization and the minimum spanning tree problem. GECCO 2021: 198-206 - [c181]Aneta Neumann, Jakob Bossek, Frank Neumann:
Diversifying greedy sampling and evolutionary diversity optimisation for constrained monotone submodular functions. GECCO 2021: 261-269 - [c180]Jakob Bossek, Aneta Neumann, Frank Neumann:
Breeding diverse packings for the knapsack problem by means of diversity-tailored evolutionary algorithms. GECCO 2021: 556-564 - [c179]Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann:
Analysis of evolutionary diversity optimisation for permutation problems. GECCO 2021: 574-582 - [c178]Adel Nikfarjam, Jakob Bossek, Aneta Neumann, Frank Neumann:
Entropy-based evolutionary diversity optimisation for the traveling salesperson problem. GECCO 2021: 600-608 - [c177]Aneta Neumann, Frank Neumann, Chao Qian:
Evolutionary submodular optimisation. GECCO Companion 2021: 918-940 - [c176]Yue Xie, Aneta Neumann, Frank Neumann:
Heuristic strategies for solving complex interacting stockpile blending problem with chance constraints. GECCO 2021: 1079-1087 - [c175]Yue Xie, Aneta Neumann, Frank Neumann, Andrew M. Sutton:
Runtime analysis of RLS and the (1+1) EA for the chance-constrained knapsack problem with correlated uniform weights. GECCO 2021: 1187-1194 - [c174]William Reid, Aneta Neumann, Simon Ratcliffe, Frank Neumann:
Advanced mine optimisation under uncertainty using evolution. GECCO Companion 2021: 1605-1613 - [c173]Chao Bian, Chao Qian, Frank Neumann, Yang Yu:
Fast Pareto Optimization for Subset Selection with Dynamic Cost Constraints. IJCAI 2021: 2191-2197 - [c172]Jakob Bossek, Aneta Neumann, Frank Neumann:
Exact Counting and Sampling of Optima for the Knapsack Problem. LION 2021: 40-54 - [c171]Hirad Assimi, Ben Koch, Chris Garcia, Markus Wagner, Frank Neumann:
Modelling and optimization of run-of-mine stockpile recovery. SAC 2021: 450-458 - [c170]Tobias Friedrich, Frank Neumann, Ralf Rothenberger, Andrew M. Sutton:
Solving Non-uniform Planted and Filtered Random SAT Formulas Greedily. SAT 2021: 188-206 - [i97]William Reid, Aneta Neumann, Simon Ratcliffe, Frank Neumann:
Advanced Ore Mine Optimisation under Uncertainty Using Evolution. CoRR abs/2102.05235 (2021) - [i96]Yue Xie, Aneta Neumann, Frank Neumann:
Heuristic Strategies for Solving Complex Interacting Stockpile Blending Problem with Chance Constraints. CoRR abs/2102.05303 (2021) - [i95]Yue Xie, Aneta Neumann, Frank Neumann, Andrew M. Sutton:
Runtime Analysis of RLS and the (1+1) EA for the Chance-constrained Knapsack Problem with Correlated Uniform Weights. CoRR abs/2102.05778 (2021) - [i94]Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann:
Analysis of Evolutionary Diversity Optimisation for Permutation Problems. CoRR abs/2102.11469 (2021) - [i93]Derek Weber, Frank Neumann:
A General Method to Find Highly Coordinating Communities in Social Media through Inferred Interaction Links. CoRR abs/2103.03409 (2021) - [i92]Yue Xie, Aneta Neumann, Frank Neumann:
Heuristic Strategies for Solving Complex Interacting Large-Scale Stockpile Blending Problems. CoRR abs/2104.03440 (2021) - [i91]Jakob Bossek, Aneta Neumann, Frank Neumann:
Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms. CoRR abs/2104.13133 (2021) - [i90]Adel Nikfarjam, Jakob Bossek, Aneta Neumann, Frank Neumann:
Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem. CoRR abs/2104.13538 (2021) - [i89]Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt:
Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. CoRR abs/2105.12525 (2021) - [i88]Jakob Bossek, Aneta Neumann, Frank Neumann:
Exact Counting and Sampling of Optima for the Knapsack Problem. CoRR abs/2106.07412 (2021) - [i87]Adel Nikfarjam, Jakob Bossek, Aneta Neumann, Frank Neumann:
Computing Diverse Sets of High Quality TSP Tours by EAX-Based Evolutionary Diversity Optimisation. CoRR abs/2108.05005 (2021) - [i86]Frank Neumann, Carsten Witt:
Runtime Analysis of Single- and Multi-Objective Evolutionary Algorithms for Chance Constrained Optimization Problems with Normally Distributed Random Variables. CoRR abs/2109.05799 (2021) - [i85]Feng Shi, Frank Neumann, Jianxin Wang:
Time Complexity Analysis of Evolutionary Algorithms for 2-Hop (1, 2)-Minimum Spanning Tree Problem. CoRR abs/2110.04701 (2021) - [i84]Hirad Assimi, Frank Neumann, Markus Wagner, Xiaodong Li:
Novelty-Driven Binary Particle Swarm Optimisation for Truss Optimisation Problems. CoRR abs/2112.07875 (2021) - [i83]Adel Nikfarjam, Aneta Neumann, Frank Neumann:
On the Use of Quality Diversity Algorithms for The Traveling Thief Problem. CoRR abs/2112.08627 (2021) - [i82]Hirad Assimi, Ben Koch, Chris Garcia, Markus Wagner, Frank Neumann:
Run-of-Mine Stockyard Recovery Scheduling and Optimisation for Multiple Reclaimers. CoRR abs/2112.12294 (2021) - [i81]Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen:
Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs. CoRR abs/2112.13175 (2021) - 2020
- [j56]Feng Shi, Martin Schirneck, Tobias Friedrich, Timo Kötzing, Frank Neumann:
Correction to: Reoptimization Time Analysis of Evolutionary Algorithms on Linear Functions Under Dynamic Uniform Constraints. Algorithmica 82(10): 3117-3123 (2020) - [j55]Behrooz Ghasemishabankareh, Xiaodong Li, Melih Ozlen, Frank Neumann:
Probabilistic tree-based representation for solving minimum cost integer flow problems with nonlinear non-convex cost functions. Appl. Soft Comput. 86 (2020) - [j54]Aneta Neumann, Bradley Alexander, Frank Neumann:
Evolutionary Image Transition and Painting Using Random Walks. Evol. Comput. 28(4): 643-675 (2020) - [j53]Tat-Jun Chin, Zhipeng Cai, Frank Neumann:
Robust Fitting in Computer Vision: Easy or Hard? Int. J. Comput. Vis. 128(3): 575-587 (2020) - [j52]Tobias Friedrich, Timo Kötzing, J. A. Gregor Lagodzinski, Frank Neumann, Martin Schirneck:
Analysis of the (1 + 1) EA on subclasses of linear functions under uniform and linear constraints. Theor. Comput. Sci. 832: 3-19 (2020) - [j51]Mojgan Pourhassan, Vahid Roostapour, Frank Neumann:
Runtime analysis of RLS and (1 + 1) EA for the dynamic weighted vertex cover problem. Theor. Comput. Sci. 832: 20-41 (2020) - [j50]Edgar Covantes Osuna, Wanru Gao, Frank Neumann, Dirk Sudholt:
Design and analysis of diversity-based parent selection schemes for speeding up evolutionary multi-objective optimisation. Theor. Comput. Sci. 832: 123-142 (2020) - [c169]Benjamin Doerr, Carola Doerr, Aneta Neumann, Frank Neumann, Andrew M. Sutton:
Optimization of Chance-Constrained Submodular Functions. AAAI 2020: 1460-1467 - [c168]Derek Weber, Frank Neumann:
Who's in the Gang? Revealing Coordinating Communities in Social Media. ASONAM 2020: 89-93 - [c167]Maryam Hasani-Shoreh, Renato Hermoza Aragonés, Frank Neumann:
Neural Networks in Evolutionary Dynamic Constrained Optimization: Computational Cost and Benefits. ECAI 2020: 275-282 - [c166]Hirad Assimi, Oscar Harper, Yue Xie, Aneta Neumann, Frank Neumann:
Evolutionary Bi-Objective Optimization for the Dynamic Chance-Constrained Knapsack Problem Based on Tail Bound Objectives. ECAI 2020: 307-314 - [c165]Vanja Doskoc, Tobias Friedrich, Andreas Göbel, Aneta Neumann, Frank Neumann, Francesco Quinzan:
Non-Monotone Submodular Maximization with Multiple Knapsacks in Static and Dynamic Settings. ECAI 2020: 435-442 - [c164]Yue Xie, Aneta Neumann, Frank Neumann:
Specific single- and multi-objective evolutionary algorithms for the chance-constrained knapsack problem. GECCO 2020: 271-279 - [c163]Vahid Roostapour, Jakob Bossek, Frank Neumann:
Runtime analysis of evolutionary algorithms with biased mutation for the multi-objective minimum spanning tree problem. GECCO 2020: 551-559 - [c162]Anh Viet Do, Jakob Bossek, Aneta Neumann, Frank Neumann:
Evolving diverse sets of tours for the travelling salesperson problem. GECCO 2020: 681-689 - [c161]Aneta Neumann, Frank Neumann:
Evolutionary computation for digital art. GECCO Companion 2020: 901-926 - [c160]Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt:
More effective randomized search heuristics for graph coloring through dynamic optimization. GECCO 2020: 1277-1285 - [c159]Jakob Bossek, Katrin Casel, Pascal Kerschke, Frank Neumann:
The node weight dependent traveling salesperson problem: approximation algorithms and randomized search heuristics. GECCO 2020: 1286-1294 - [c158]Ragav Sachdeva, Frank Neumann, Markus Wagner:
The Dynamic Travelling Thief Problem: Benchmarks and Performance of Evolutionary Algorithms. ICONIP (5) 2020: 220-228 - [c157]Jakob Bossek, Carola Doerr, Pascal Kerschke, Aneta Neumann, Frank Neumann:
Evolving Sampling Strategies for One-Shot Optimization Tasks. PPSN (1) 2020: 111-124 - [c156]Jakob Bossek, Aneta Neumann, Frank Neumann:
Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions. PPSN (1) 2020: 346-359 - [c155]Aneta Neumann, Frank Neumann:
Optimising Monotone Chance-Constrained Submodular Functions Using Evolutionary Multi-objective Algorithms. PPSN (1) 2020: 404-417 - [c154]Anh Viet Do, Frank Neumann:
Maximizing Submodular or Monotone Functions Under Partition Matroid Constraints by Multi-objective Evolutionary Algorithms. PPSN (2) 2020: 588-603 - [c153]Maryam Hasani-Shoreh, Renato Hermoza Aragonés, Frank Neumann:
Using Neural Networks and Diversifying Differential Evolution for Dynamic Optimisation. SSCI 2020: 289-296 - [c152]Aneta Neumann, Frank Neumann:
Human Interactive EEG-Based Evolutionary Image Animation. SSCI 2020: 678-685 - [p6]Frank Neumann, Andrew M. Sutton:
Parameterized Complexity Analysis of Randomized Search Heuristics. Theory of Evolutionary Computation 2020: 213-248 - [p5]