Prof Frank Neumann
Professor
School of Computer Science and Information Technology
College of Engineering and Information Technology
Eligible to supervise Masters and PhD - email supervisor to discuss availability.
Frank Neumann is a professor and the leader of the Optimisation and Logistics group at the University of Adelaide. He is an expert in the field of evolutionary computation and AI-based optimisation. Frank received a Humboldt Fellowship for Experienced Researchers in 2019, an Australian Research Council Future Fellowship in 2020, and the ACM SIGEVO Outstanding Contribution Award in 2025. He has been the general chair of the ACM GECCO 2016 and co-organised ACM FOGA 2013 in Adelaide. He is an Area Editor of the journal "ACM Transactions on Evolutionary Learning and Optimization" and an Associate Editor of the journal "Evolutionary Computation" (MIT Press). In his work, he considers algorithmic approaches in particular for combinatorial and multi-objective optimization problems and focuses on theoretical aspects of evolutionary computation as well as high impact applications in the areas of cybersecurity, renewable energy, logistics, and mining.
- artificial intelligence
- bio-inspired computing
- cybersecurity
- machine learning
- optimization
- renewable energy
- supply chain management
| Date | Position | Institution name |
|---|---|---|
| 2016 - ongoing | Professor | The University of Adelaide |
| 2015 - 2016 | Associate Dean (Research) | The University of Adelaide |
| 2013 - 2015 | Associate Professor | The University of Adelaide |
| 2011 - 2012 | Senior Lecturer | The University of Adelaide |
| 2008 - 2010 | Coordinator of the group "Bio-Inspired Computation” | Max Planck Institute for Informatics (MPG) |
| 2006 - 2008 | Postdoctoral Researcher | Max Planck Institute for Informatics (MPG) |
| 2002 - 2006 | Research Assistant | Kiel University |
| Date | Institution name | Country | Title |
|---|---|---|---|
| 2006 | Kiel University | Germany | PhD |
| 2002 | Kiel University | Germany | Diplom |
| Year | Citation |
|---|---|
| 2025 | Neumann, F., & Witt, C. (2025). Runtime Analysis of Single- and Multi-Objective Evolutionary Algorithms for Chance Constrained Optimization Problems with Normally Distributed Random Variables. Evolutionary Computation, 33(2), 191-214. |
| 2025 | Antipov, D., Neumann, A., Neumann, F., & Sutton, A. M. (2025). Runtime Analysis of Evolutionary Diversity Optimization on the Multi-objective (LeadingOnes, TrailingZeros) Problem.. Evolutionary computation, 1-23. |
| 2025 | Shi, F., Huang, D., Yan, X., & Neumann, F. (2025). Runtime performance of evolutionary algorithms for the chance-constrained makespan scheduling problem. Theoretical Computer Science, 1044, 28 pages. |
| 2025 | Neumann, F., Sudholt, D., & Witt, C. (2025). The Compact Genetic Algorithm Struggles on Cliff Functions.. Algorithmica, 87, 507-536. |
| 2025 | Xu, M., Neumann, F., Neumann, A., & Ong, Y. S. (2025). Quality Diversity Genetic Programming for Learning Scheduling Heuristics.. CoRR, abs/2507.02235. |
| 2025 | Goel, D., Ward, M., Neumann, A., Neumann, F., Nguyen, H. X., & Guo, M. (2025). Hardening Active Directory Graphs via Evolutionary Diversity Optimization-based Policies.. ACM Trans. Evol. Learn. Optim., 5, 19:1. |
| 2025 | Neumann, F., & Witt, C. (2025). Fast Pareto Optimization Using Sliding Window Selection for Problems with Determinstic and Stochastic Constraints.. Evolutionary computation, 1-34. |
| 2025 | Baguley, S., Friedrich, T., Neumann, A., Neumann, F., Pappik, M., & Zeif, Z. (2025). Fixed Parameter Multi-Objective Evolutionary Algorithms for the W-Separator Problem. Algorithmica, 87(4), 537-571. Scopus1 |
| 2025 | Pan, S., Patel, Y. J., Neumann, A., Neumann, F., Bäck, T., & Wang, H. (2025). Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms. Gecco 2025 Proceedings of the 2025 Genetic and Evolutionary Computation Conference, abs/2502.12012, 443-452. |
| 2025 | Goel, D., Ward, M., Neumann, A., Neumann, F., Nguyen, H., & Guo, M. (2025). Hardening Active Directory Graphs via Evolutionary Diversity Optimization based Policies. ACM Transactions on Evolutionary Learning and Optimization, 5(3), 1-36. Scopus2 |
| 2025 | Friedrich, T., Kötzing, T., Neumann, A., Neumann, F., & Radhakrishnan, A. (2025). Analysis of the (1+1) EA on LeadingOnes with Constraints. Algorithmica, 87(5), 661-689. |
| 2024 | Nikfarjam, A., Neumann, A., & Neumann, F. (2024). On the Use of Quality Diversity Algorithms for the Travelling Thief Problem.. ACM Trans. Evol. Learn. Optim., 4, 12. |
| 2024 | Ghasemi, Z., Neshat, M., Aldrich, C., Karageorgos, J., Zanin, M., Neumann, F., & Chen, L. (2024). An integrated intelligent framework for maximising SAG mill throughput: Incorporating expert knowledge, machine learning and evolutionary algorithms for parameter optimisation. Minerals Engineering, 212(108733), 108733-1-108733-16. Scopus9 WoS10 |
| 2024 | Santoni, M. L., Raponi, E., Neumann, A., Neumann, F., Preuss, M., & Doerr, C. (2024). Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization.. CoRR, abs/2408.16393, 1-21. |
| 2024 | Dang, D. -C., Neumann, A., Neumann, F., Opris, A., & Sudholt, D. (2024). Theoretical Analysis of Quality Diversity Algorithms for a Classical Path Planning Problem.. CoRR, abs/2412.11446. |
| 2024 | van Meerten, T., Kuruvilla, J., Song, K. W., Thieblemont, C., Minnema, M. C., Forcade, E., . . . Topp, M. S. (2024). Original Impact of debulking therapy on the clinical outcomes of axicabtagene ciloleucel in the treatment of relapsed or refractory large B-cell lymphoma. AMERICAN JOURNAL OF CANCER RESEARCH, 14(6), 25 pages. |
| 2024 | Elbert, M., Neumann, F., Kiefer, M., Christofyllakis, K., Balensiefer, B., Kos, I., . . . Bewarder, M. (2024). Hyper-N-glycosylated SEL1L3 as auto-antigenic B-cell receptor target of primary vitreoretinal lymphomas. SCIENTIFIC REPORTS, 14(1), 13 pages. WoS2 |
| 2024 | Ahouei, S. S., Nobel, J. D., Neumann, A., Bäck, T., & Neumann, F. (2024). Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem.. CoRR, abs/2405.18772. |
| 2024 | Neumann, F., & Sutton, A. M. (2024). Editor's Note: Special Issue with GECCO 2021. ALGORITHMICA, 86(6), 1 page. |
| 2024 | Nikfarjam, A., Neumann, A., & Neumann, F. (2024). On the Use of Quality Diversity Algorithms for The Traveling Thief Problem.. ACM Transactions on Evolutionary Learning and Optimization, 4(2), 1-22. Scopus5 |
| 2024 | Neumann, F., Sudholt, D., & Witt, C. (2024). The Compact Genetic Algorithm Struggles on Cliff Functions. Algorithmica: an international journal in computer science, 87(4), 507-536. Scopus1 WoS1 |
| 2024 | Ghasemi, Z., Neumann, F., Zanin, M., Karageorgos, J., & Chen, L. (2024). A comparative study of prediction methods for semi-autogenous grinding mill throughput. Minerals Engineering, 205(108458), 108458-1-108458-14. Scopus13 WoS12 |
| 2023 | Perera, K., Neumann, A., & Neumann, F. (2023). Evolutionary Multi-Objective Algorithms for the Knapsack Problems with Stochastic Profits. CoRR, abs/2303.01695. |
| 2023 | Ye, F., Neumann, F., Nobel, J. D., Neumann, A., & Bäck, T. (2023). What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms. CoRR, abs/2303.04611. |
| 2023 | Stimson, M., Reid, W., Neumann, A., Ratcliffe, S., & Neumann, F. (2023). Improving Confidence in Evolutionary Mine Scheduling via Uncertainty Discounting. 2023 IEEE Congress on Evolutionary Computation, CEC 2023, abs/2305.17957, 1-10. Scopus3 |
| 2023 | Balu, D., Valencia-Olvera, A. C., Nguyen, A., Patnam, M., York, J., Peri, F., . . . Tai, L. M. (2023). A small-molecule TLR4 antagonist reduced neuroinflammation in female E4FAD mice. ALZHEIMERS RESEARCH & THERAPY, 15(1), 15 pages. WoS15 |
| 2022 | Roostapour, V., Neumann, A., Neumann, F., & Friedrich, T. (2022). Pareto optimization for subset selection with dynamic cost constraints.. Artif. Intell., 302, 103597. |
| 2022 | Bossek, J., & Neumann, F. (2022). Exploring the Feature Space of TSP Instances Using Quality Diversity.. CoRR, abs/2202.02077. |
| 2022 | Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2022). Niching-based Evolutionary Diversity Optimization for the Traveling Salesperson Problem.. CoRR, abs/2201.10316. |
| 2022 | Friedrich, T., Kötzing, T., Neumann, F., & Radhakrishnan, A. (2022). Theoretical Study of Optimizing Rugged Landscapes with the cGA.. CoRR, abs/2211.13801. |
| 2022 | Lengler, J., & Neumann, F. (2022). Editorial.. Algorithmica, 84, 1571-1572. |
| 2022 | Roostapour, V., Neumann, A., & Neumann, F. (2022). Single- and multi-objective evolutionary algorithms for the knapsack problem with dynamically changing constraints.. Theor. Comput. Sci., 924, 129-147. |
| 2022 | Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2022). Analysis of Evolutionary Diversity Optimization for Permutation Problems.. ACM Trans. Evol. Learn. Optim., 2, 11:1. |
| 2022 | Roostapour, V., Neumann, A., Neumann, F., & Friedrich, T. (2022). Pareto optimization for subset selection with dynamic cost constraints. Artificial Intelligence, 302, 103597-1-103597-17. Scopus41 WoS29 |
| 2022 | Dumuid, D., Olds, T., Wake, M., Lund Rasmussen, C., Pedišić, Ž., Hughes, J. H., . . . Stanford, T. (2022). Your best day: An interactive app to translate how time reallocations within a 24-hour day are associated with health measures. PLoS One, 17(9), e0272343-1-e0272343-16. Scopus12 WoS11 Europe PMC9 |
| 2022 | Roostapour, V., Neumann, A., & Neumann, F. (2022). Single- and multi-objective evolutionary algorithms for the knapsack problem with dynamically changing constraints. Theoretical Computer Science, 924, 129-147. Scopus11 WoS10 |
| 2021 | Neumann, F., Pourhassan, M., & Witt, C. (2021). Improved runtime results for simple randomised search heuristics on linear functions with a uniform constraint. Algorithmica, 83(10), 3209-3237. Scopus4 WoS13 |
| 2021 | Doerr, B., & Neumann, F. (2021). A Survey on Recent Progress in the Theory of Evolutionary Algorithms for Discrete Optimization. ACM Transactions on Evolutionary Learning and Optimization, 1(4), 16-1-16-43. Scopus34 |
| 2021 | Shi, F., Neumann, F., & Wang, J. (2021). Time complexity analysis of evolutionary algorithms for 2-hop (1,2)-minimum spanning tree problem. Theoretical Computer Science, 893, 159-175. Scopus5 WoS3 |
| 2021 | Weber, D., & Neumann, F. (2021). Amplifying influence through coordinated behaviour in social networks. Social Network Analysis and Mining, 11(1), 1-42. Scopus53 Europe PMC8 |
| 2021 | Assenmacher, D., Weber, D., Preuss, M., Calero Valdez, A., Bradshaw, A., Ross, B., . . . Grimme, C. (2021). Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem. Social Science Computer Review, 40(6), 089443932110122. Scopus19 WoS17 |
| 2021 | Bossek, J., Neumann, F., Peng, P., & Sudholt, D. (2021). Time complexity analysis of randomized search heuristics for the dynamic graph coloring problem. Algorithmica, 83(10), 3148-3179. Scopus4 WoS13 |
| 2021 | Weber, D., & Neumann, F. (2021). A General Method to Find Highly Coordinating Communities in Social Media through Inferred Interaction Links.. CoRR, abs/2103.03409(1), 42 pages. WoS36 |
| 2021 | Shi, F., Neumann, F., & Wang, J. (2021). Runtime Performances of Randomized Search Heuristics for the Dynamic Weighted Vertex Cover Problem. Algorithmica: an international journal in computer science, 83, 906-939. |
| 2021 | Guo, M., Li, J., Neumann, A., Neumann, F., & Nguyen, H. (2021). Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs.. CoRR, abs/2112.13175. |
| 2021 | Neumann, A., Alexander, B., & Neumann, F. (2021). Evolutionary Image Transition and Painting Using Random Walks. Evolutionary Computation, 28(4), 643-675. |
| 2021 | Shi, F., Neumann, F., & Wang, J. (2021). Time Complexity Analysis of Evolutionary Algorithms for 2-Hop (1, 2)-Minimum Spanning Tree Problem.. CoRR, abs/2110.04701. |
| 2021 | Assimi, H., Koch, B., Garcia, C., Wagner, M., & Neumann, F. (2021). Run-of-Mine Stockyard Recovery Scheduling and Optimisation for Multiple Reclaimers.. CoRR, abs/2112.12294. |
| 2021 | Assimi, H., Neumann, F., Wagner, M., & Li, X. (2021). Novelty-Driven Binary Particle Swarm Optimisation for Truss Optimisation Problems.. CoRR, abs/2112.07875. |
| 2021 | Bossek, J., Neumann, F., Peng, P., & Sudholt, D. (2021). Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem.. Algorithmica, 83, 3148-3179. |
| 2021 | Neumann, F., Pourhassan, M., & Witt, C. (2021). Improved Runtime Results for Simple Randomised Search Heuristics on Linear Functions with a Uniform Constraint.. Algorithmica, 83, 3209-3237. |
| 2021 | Doerr, B., & Neumann, F. (2021). A Survey on Recent Progress in the Theory of Evolutionary Algorithms for Discrete Optimization.. ACM Trans. Evol. Learn. Optim., 1, 16:1. |
| 2020 | Mechau, J., & Neumann, F. (2020). Small Water Projects, big Impact. WASSERWIRTSCHAFT, 110(9), 57-58. |
| 2020 | Ziemer, I., & Neumann, F. (2020). Photocatalytic reduction of nitrogen oxides - Numerical simulation for verification of efficiency. VAKUUM IN FORSCHUNG UND PRAXIS, 32(5), 42-44. |
| 2020 | Neumann, A., Alexander, B., & Neumann, F. (2020). Evolutionary Image Transition and Painting Using Random Walks. Evolutionary Computation, 28(4), 643-675. Scopus12 WoS9 |
| 2020 | Chin, T. -J., Cai, Z., & Neumann, F. (2020). Robust fitting in computer vision: Easy or hard?. International Journal of Computer Vision, 128(3), 575-587. Scopus21 WoS17 |
| 2020 | Shi, F., Neumann, F., & Wang, J. (2020). Runtime Performances of Randomized Search Heuristics for the Dynamic Weighted Vertex Cover Problem. Algorithmica, 83(4), 906-939. Scopus6 WoS6 |
| 2020 | Do, A. V., & Neumann, F. (2020). Pareto Optimization for Subset Selection with Dynamic Partition Matroid Constraints.. CoRR, abs/2012.08738. |
| 2020 | Neumann, A., Bossek, J., & Neumann, F. (2020). Computing Diverse Sets of Solutions for Monotone Submodular Optimisation Problems.. CoRR, abs/2010.11486. |
| 2020 | Friedrich, T., Kötzing, T., Lagodzinski, J. A. G., Neumann, F., & Schirneck, M. (2020). Analysis of the (1 + 1) EA on subclasses of linear functions under uniform and linear constraints. Theoretical Computer Science, 832, 3-19. Scopus14 WoS13 |
| 2020 | Pourhassan, M., Roostapour, V., & Neumann, F. (2020). Runtime analysis of RLS and (1+1) EA for the dynamic weighted vertex cover problem. Theoretical Computer Science, 832, 20-41. Scopus5 WoS4 |
| 2020 | Ghasemishabankareh, B., Li, X., Ozlen, M., & Neumann, F. (2020). Probabilistic tree-based representation for solving minimum cost integer flow problems with nonlinear non-convex cost functions. Applied Soft Computing Journal, 86, 14 pages. Scopus2 WoS2 |
| 2019 | Bossek, J., Kerschke, P., Neumann, A., Neumann, F., & Doerr, C. (2019). One-Shot Decision-Making with and without Surrogates.. CoRR, abs/1912.08956. |
| 2019 | Kerschke, P., Hoos, H. H., Neumann, F., & Trautmann, H. (2019). Automated Algorithm Selection: Survey and Perspectives.. Evol. Comput., 27, 3-45. |
| 2019 | Shi, F., Schirneck, M., Friedrich, T., Kötzing, T., & Neumann, F. (2019). Reoptimization Time Analysis of Evolutionary Algorithms on Linear Functions Under Dynamic Uniform Constraints.. Algorithmica, 81(10), 828-857. Scopus2 WoS2 |
| 2019 | Bustos, Á. P., Chin, T. -J., Neumann, F., Friedrich, T., & Katzmann, M. (2019). A Practical Maximum Clique Algorithm for Matching with Pairwise Constraints.. CoRR, abs/1902.01534. |
| 2019 | Pourhassan, M., Shi, F., & Neumann, F. (2019). Parameterized analysis of multiobjective evolutionary algorithms and the weighted vertex cover problem. Evolutionary Computation, 27(4), 559-575. Scopus8 WoS7 Europe PMC1 |
| 2019 | Kerschke, P., Hoos, H. H., Neumann, F., & Trautmann, H. (2019). Automated algorithm selection: survey and perspectives. Evolutionary Computation, 27(1), 3-45. Scopus384 WoS311 Europe PMC8 |
| 2019 | Pourhassan, M., & Neumann, F. (2019). Theoretical analysis of local search and simple evolutionary algorithms for the generalized travelling salesperson problem. Evolutionary Computation, 27(3), 525-558. Scopus5 WoS1 |
| 2019 | Azevedo, I. C., Duarte, P. M., Marinho, G. S., Neumann, F., & Sousa-Pinto, I. (2019). Growth of <i>Saccharina latissima</i> (Laminariales, Phaeophyceae) cultivated offshore under exposed conditions. PHYCOLOGIA, 58(5), 504-515. WoS30 |
| 2019 | Dalton, G., Bardocz, T., Blanch, M., Campbell, D., Johnson, K., Lawrence, G., . . . Masters, I. (2019). Feasibility of investment in Blue Growth multiple-use of space and multi-use platform projects; results of a novel assessment approach and case studies. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 107, 338-359. WoS52 |
| 2019 | Doskoc, V., Friedrich, T., Göbel, A., Neumann, F., Neumann, A., & Quinzan, F. (2019). Non-Monotone Submodular Maximization with Multiple Knapsacks in Static and Dynamic Settings.. CoRR, abs/1911.06791. |
| 2019 | Shi, F., Schirneck, M., Friedrich, T., Kötzing, T., & Neumann, F. (2019). Reoptimization Time Analysis of Evolutionary Algorithms on Linear Functions Under Dynamic Uniform Constraints. Algorithmica, 81(2), 1-30. Scopus18 WoS15 |
| 2018 | Covantes Osuna, E., Gao, W., Neumann, F., & Sudholt, D. (2018). Design and analysis of diversity-based parent selection schemes for speeding up evolutionary multi-objective optimisation. Theoretical Computer Science, 832, 123-142. Scopus36 WoS32 |
| 2018 | Neumann, F., & Atten, M. (2018). Novel approach for shape-based similarity search enabled by 3D PDF. INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 58(2), 165-173. WoS5 |
| 2017 | Doerr, B., Neumann, F., & Sutton, A. (2017). Time Complexity Analysis of Evolutionary Algorithms on Random Satisfiable k-CNF Formulas. Algorithmica, 78(2), 561-586. Scopus17 WoS14 |
| 2017 | Bonyadi, M., Michalewicz, Z., Nallaperuma, S., & Neumann, F. (2017). Ahura: a heuristic-based racer for the open racing car simulator. IEEE Transactions on Computational Intelligence and AI in Games, 9(3), 290-304. Scopus13 WoS7 |
| 2017 | Nallaperuma, S., Neumann, F., & Sudholt, D. (2017). Expected Fitness Gains of Randomized Search Heuristics for the Traveling Salesperson Problem. Evolutionary Computation, 25(4), 673-705. Scopus21 WoS19 Europe PMC1 |
| 2017 | Polyakovskiy, S., & Neumann, F. (2017). The Packing While Traveling Problem. European Journal of Operational Research, 258(2), 424-439. Scopus15 WoS13 |
| 2016 | Keating, C. B., & Ireland, V. (2016). Editorial. International Journal of System of Systems Engineering, 7(1/2/3), 1-21. Scopus6 |
| 2016 | Polyakovskiy, S., Berghammer, R., & Neumann, F. (2016). Solving hard control problems in voting systems via integer programming. European Journal of Operational Research, 250(1), 204-213. Scopus4 WoS3 |
| 2016 | Hoos, H. H., Neumann, F., & Trautmann, H. (2016). Automated Algorithm Selection and Configuration (Dagstuhl Seminar 16412).. Dagstuhl Reports, 6, 33-74. |
| 2016 | Bonyadi, M. R., Michalewicz, Z., Neumann, F., & Wagner, M. (2016). Evolutionary computation for multicomponent problems: opportunities and future directions.. CoRR, abs/1606.06818. |
| 2016 | Corus, D., Lehre, P., Neumann, F., & Pourhassan, M. (2016). A Parameterised Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms. Evolutionary Computation, 24(1), 183-203. Scopus17 WoS16 Europe PMC1 |
| 2016 | Kaufmann, P., Kramer, O., Neumann, F., & Wagner, M. (2016). Optimization methods in renewable energy systems design. Renewable Energy, 87, 835-836. Scopus4 WoS4 |
| 2015 | Friedrich, T., & Neumann, F. (2015). Maximizing submodular functions under matroid constraints by evolutionary algorithms. Evolutionary Computation, 23(4), 543-558. Scopus82 WoS75 Europe PMC2 |
| 2015 | Nallaperuma, S., Wagner, M., & Neumann, F. (2015). Analyzing the effects of instance features and algorithm parameters for max-min ant system and the traveling salesperson problem. Frontiers in Robotics and AI, 2(JUL), 18-1-18-16. Scopus24 WoS20 |
| 2015 | Friedrich, T., Neumann, F., & Thyssen, C. (2015). Multiplicative approximations, optimal hypervolume distributions, and the choice of the reference point. Evolutionary Computation, 23(1), 131-159. Scopus13 WoS12 Europe PMC1 |
| 2015 | Wagner, M., Neumann, F., & Urli, T. (2015). On the performance of different genetic programming approaches for the SORTING problem. Evolutionary Computation, 23(4), 583-609. Scopus6 WoS5 |
| 2015 | Nguyen, A., Sutton, A., & Neumann, F. (2015). Population size matters: rigorous runtime results for maximizing the hypervolume indicator. Theoretical Computer Science, 561(Part A), 24-36. Scopus27 WoS26 |
| 2015 | Wagner, M., Bringmann, K., Friedrich, T., & Neumann, F. (2015). Efficient optimization of many objectives by approximation-guided evolution. European Journal of Operational Research, 243(2), 465-479. Scopus27 WoS23 |
| 2015 | Polyakovskiy, S., & Neumann, F. (2015). The Packing While Traveling Problem.. CoRR, abs/1512.08831. |
| 2014 | Mei, H., Neumann, F., Yao, X., & Minku, L. L. (2014). Computational Intelligence for Software Engineering (NII Shonan Meeting 2014-13).. NII Shonan Meet. Rep., 2014. |
| 2014 | Kötzing, T., Sutton, A., Neumann, F., & O'Reilly, U. (2014). The Max problem revisited: The importance of mutation in genetic programming. Theoretical Computer Science, 545(C), 94-107. Scopus15 WoS12 |
| 2014 | Neumann, F., Doerr, B., Lehre, P. K., & Haddow, P. C. (2014). Editorial for the special issue on theoretical foundations of evolutionary computation. IEEE Transactions on Evolutionary Computation, 18(5), 625-627. |
| 2014 | Sutton, A. M., Neumann, F., & Nallaperuma, S. (2014). Parameterized runtime analyses of evolutionary algorithms for the planar Euclidean traveling salesperson problem. Evolutionary Computation, 22(4), 595-628. Scopus32 WoS25 Europe PMC1 |
| 2013 | Friedrich, T., Kroeger, T., & Neumann, F. (2013). Weighted preferences in evolutionary multi-objective optimization. International Journal of Machine Learning and Cybernetics, 4(2), 139-148. Scopus17 WoS16 |
| 2013 | Kratsch, S., & Neumann, F. (2013). Fixed-parameter evolutionary algorithms and the vertex cover problem. Algorithmica, 65(4), 754-771. Scopus70 WoS58 |
| 2013 | Doerr, B., Johannsen, D., Kotzing, T., Neumann, F., & Theile, M. (2013). More effective crossover operators for the all-pairs shortest path problem. Theoretical Computer Science, 471, 12-26. Scopus40 WoS36 |
| 2013 | Wagner, M., Day, J., & Neumann, F. (2013). A fast and effective local search algorithm for optimizing the placement of wind turbines. Renewable Energy, 51, 64-70. Scopus98 WoS92 |
| 2013 | Vladislavleva, E., Friedrich, T., Neumann, F., & Wagner, M. (2013). Predicting the energy output of wind farms based on weather data: important variables and their correlation. Renewable Energy, 50, 236-243. Scopus93 WoS77 |
| 2013 | Mersmann, O., Bischl, B., Trautmann, H., Wagner, M., Bossek, J., & Neumann, F. (2013). A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem. Annals of Mathematics and Artificial Intelligence, 69(2), 151-182. Scopus78 WoS57 |
| 2013 | Doerr, B., Eremeev, A. V., Neumann, F., Theile, M., & Thyssen, C. (2013). Evolutionary Algorithms and Dynamic Programming. CoRR, abs/1301.4096. |
| 2013 | Koerner, R., Preuss, K. -D., Fadle, N., Madjidi, D., Neumann, F., Bergeler, L., . . . Pfoehler, C. (2013). Serum Antibodies against CD28-A New Potential Marker of Dismal Prognosis in Melanoma Patients. PLOS ONE, 8(3), 10 pages. |
| 2013 | Boettger, M., Graumann, T., Boughaled, R., Neumann, F., Jones, P. G., Kowalsky, W., & Johannes, H. -H. (2013). Development of a new qualification method for photocatalytically active surfaces based on a solid state luminescent dye (vol 253, pg 7, 2013). JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY A-CHEMISTRY, 272, 100. |
| 2013 | Arlt, G., Neumann, F., & Milkau, U. (2013). A simple model for pseudo-nonstationarity in operational risk loss data due to interest rate dependency and reporting threshold. JOURNAL OF OPERATIONAL RISK, 8(4), 27-37. WoS3 |
| 2013 | Mills, A., Hepburn, J., Hazafy, D., O'Rourke, C., Krysa, J., Baudys, M., . . . Graumann, T. (2013). A simple, inexpensive method for the rapid testing of the photocatalytic activity of self-cleaning surfaces. JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY A-CHEMISTRY, 272, 18-20. WoS53 |
| 2013 | Boettger, M., Graumann, T., Boughaled, R., Neumann, F., Jones, P. G., Kowalsky, W., & Johannes, H. -H. (2013). Development of a new qualification method for photocatalytically active surfaces based on a solid state luminescent dye (vol 253, pg 7, 2013). JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY A-CHEMISTRY, 259, 66. |
| 2013 | Boettger, M., Graumann, T., Boughaled, R., Neumann, F., Kowalsky, W., & Johannes, H. -H. (2013). Development of a new qualification method for photocatalytically active surfaces based on a solid state luminescent dye. JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY A-CHEMISTRY, 253, 7-15. WoS7 |
| 2012 | Mersmann, O., Bischl, B., Trautmann, H., Wagner, M., & Neumann, F. (2012). A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesman Problem. CoRR, abs/1208.2318. |
| 2012 | Berghammer, R., Friedrich, T., & Neumann, F. (2012). Convergence of set-based multi-objective optimization, indicators and deteriorative cycles. Theoretical Computer Science, 456, 2-17. Scopus15 WoS15 |
| 2012 | Lehre, P. K., Neumann, F., & Rowe, J. E. (2012). Editorial to the special issue on "Theoretical foundations of evolutionary computation". Theoretical Computer Science, 425, 2-3. |
| 2012 | Kotzing, T., Neumann, F., Roglin, H., & Witt, C. (2012). Theoretical analysis of two ACO approaches for the traveling salesman problem. Swarm Intelligence, 6(1), 1-21. Scopus45 WoS32 |
| 2011 | Doerr, B., Eremeev, A., Neumann, F., Theile, M., & Thyssen, C. (2011). Evolutionary algorithms and dynamic programming. Theoretical Computer Science, 412(43), 6020-6035. Scopus16 WoS10 |
| 2011 | Friedrich, T., Horoba, C., & Neumann, F. (2011). Illustration of fairness in evolutionary multi-objective optimization. Theoretical Computer Science, 412(17), 1546-1556. Scopus22 WoS18 |
| 2011 | Doerr, B., Neumann, F., Sudholt, D., & Witt, C. (2011). Runtime analysis of the 1-ANT ant colony optimizer. Theoretical Computer Science, 412(17), 1629-1644. Scopus32 WoS24 |
| 2011 | Neumann, F., Reichel, J., & Skutella, M. (2011). Computing minimum cuts by randomized search heuristics. Algorithmica (New York), 59(3), 323-342. Scopus25 WoS25 |
| 2011 | Kagan, E., Stein, M., Agnon, A., & Neumann, F. (2011). Intrabasin paleoearthquake and quiescence correlation of the late Holocene Dead Sea (vol 116, B04311, 2011). JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH, 116(B11), 2 pages. |
| 2011 | Kurz, J., Eberle, F., Graumann, T., Kaschel, M. -E., Saehr, A., Neumann, F., . . . Erdinger, L. (2011). Inactivation of LPS and RNase A on photocatalytically active surfaces. CHEMOSPHERE, 84(9), 1188-1193. WoS10 |
| 2011 | Kagan, E., Stein, M., Agnon, A., & Neumann, F. (2011). Intrabasin paleoearthquake and quiescence correlation of the late Holocene Dead Sea. JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH, 116(B4), 27 pages. WoS63 |
| 2011 | Lovdal, N., & Neumann, F. (2011). Internationalization as a strategy to overcome industry barriers-An assessment of the marine energy industry. ENERGY POLICY, 39(3), 1093-1100. WoS33 |
| 2010 | Hohenstein, C., Neumann, F., & Kornath, A. (2010). Reactivity of Tetramethylphosphonium Fluoride in Acetonitrile Solutions. ZEITSCHRIFT FUR NATURFORSCHUNG SECTION B-A JOURNAL OF CHEMICAL SCIENCES, 65(11), 1327-1333. |
| 2010 | Hohenstein, C., Kornath, A., Neumann, F., & Ludwig, R. (2010). Preparation and Properties of Dimethyltetrafluorophosphate. INORGANIC CHEMISTRY, 49(14), 6421-6427. WoS1 |
| 2010 | Friedrich, T., & Neumann, F. (2010). When to use bit-wise neutrality. Natural Computing, 9(1), 283-294. Scopus1 WoS1 |
| 2010 | Friedrich, T., He, J., Hebbinghaus, N., Neumann, F., & Witt, C. (2010). Approximating covering problems by randomized search heuristics using multi-objectivemodels. Evolutionary Computation, 18(4), 617-633. Scopus113 WoS93 Europe PMC8 |
| 2010 | Doerr, B., Neumann, F., & Wegener, I. (2010). Algorithmica (New York): Editorial. Algorithmica New York, 57(1), 119-120. |
| 2010 | Jansen, T., & Neumann, F. (2010). Editorial for the special issue on theoretical aspects of evolutionary multi-objective optimization. Evolutionary Computation, 18(3), 333-334. Scopus1 WoS1 |
| 2010 | Friedrich, T., Hebbinghaus, N., & Neumann, F. (2010). Plateaus can be harder in multi-objective optimization. Theoretical Computer Science, 411(6), 854-864. Scopus16 WoS16 |
| 2010 | Neumann, F., & Witt, C. (2010). Ant Colony Optimization and the minimum spanning tree problem. Theoretical Computer Science, 411(25), 2406-2413. Scopus58 WoS47 |
| 2009 | Doerr, B., & Neumann, F. (2009). In Memoriam: Ingo Wegener. Algorithmica (New York), 58(3), 1-2. |
| 2009 | Neumann, F., Sudholt, D., & Witt, C. (2009). Analysis of different MMAS ACO algorithms on unimodal functions and plateaus. Swarm Intelligence, 3(1), 35-68. Scopus73 |
| 2009 | Neumann, F., & Witt, C. (2009). Runtime analysis of a simple ant colony optimization algorithm. Algorithmica, 54(2), 243-255. Scopus77 WoS52 |
| 2009 | Friedrich, T., He, J., Hebbinghaus, N., Neumann, F., & Witt, C. (2009). Analyses of simple hybrid algorithms for the vertex cover problem. Evolutionary Computation, 17(1), 3-19. Scopus42 WoS36 Europe PMC1 |
| 2009 | Friedrich, T., Hebbinghaus, N., & Neumann, F. (2009). Comparison of simple diversity mechanisms on plateau functions. Theoretical Computer Science, 410(26), 2455-2462. Scopus18 WoS15 |
| 2009 | Brockhoff, D., Friedrich, T., Hebbinghaus, N., Klein, C., Neumann, F., & Zitzler, E. (2009). On the effects of adding objectives to plateau functions. IEEE Transactions on Evolutionary Computation, 13(3), 591-603. Scopus76 WoS60 |
| 2009 | Huertas-Olivares, C., & Neumann, F. (2009). Environmental Impacts of Ocean Energy Systems. WASSERWIRTSCHAFT, 99(3), 33-37. WoS1 |
| 2009 | Jansen, T., Schmidt, M., Sudholt, D., Witt, C., & Zarges, C. (2009). In Memoriam: Ingo Wegener. EVOLUTIONARY COMPUTATION, 17(1), 1-2. |
| 2008 | Neumann, F. (2008). Expected runtimes of evolutionary algorithms for the Eulerian cycle problem. Computers & Operations Research, 35(9), 2750-2759. Scopus39 WoS30 |
| 2007 | Neumann, F. (2007). Expected runtimes of a simple evolutionary algorithm for the multi-objective minimum spanning tree problem. European Journal of Operational Research, 181(3), 1620-1629. Scopus90 WoS76 |
| 2007 | Neumann, F., & Wegener, I. (2007). Randomized local search, evolutionary algorithms, and the minimum spanning tree problem. Theoretical Computer Science, 378(1), 32-40. Scopus200 WoS161 |
| 2007 | Doerr, B., Hebbinghaus, N., & Neumann, F. (2007). Speeding Up Evolutionary Algorithms through Asymmetric Mutation Operators. Evolutionary Computation, 15(4), 401-410. Scopus38 WoS33 Europe PMC2 |
| 2007 | Neumann, F., Schoelzel, C., Litt, T., Hense, A., & Stein, M. (2007). Holocene vegetation and climate history of the northern Golan heights (Near East) (vol 16, pg 329, 2007). VEGETATION HISTORY AND ARCHAEOBOTANY, 16(4), 347. WoS2 |
| 2007 | Neugebauer, M., Hilpert, U., Bartscher, M., Gerwien, N., Kunz, S., Neumann, F., . . . Weidemann, G. (2007). A geometrical standard for testing of X-ray computer tomography. TM-TECHNISCHES MESSEN, 74(11), 565-571. WoS14 |
| 2006 | Neumann, F., & Wegener, I. (2006). Minimum spanning trees made easier via multi-objective optimization. Natural Computing, 5(3), 305-319. Scopus121 |
| 1938 | Neumann, F. (1938). Introduction to Theoretical Seismology, pt 1, Geodynamics. GEOGRAPHICAL REVIEW, 28(1), 173-174. |
| - | Ghasemi, Z., Neshat, M., Aldrich, C., Karageorgos, J., Zanin, M., Neumann, F., & Chen, L. (n.d.). A Hybrid Intelligent Framework for Maximising Sag Mill Throughput: An Integration of Expert Knowledge, Machine Learning and Evolutionary Algorithms for Parameter Optimisation. |
| Year | Citation |
|---|---|
| 2020 | Doerr, B., & Neumann, F. (Eds.) (2020). Theory of Evolutionary Computation - Recent Developments in Discrete Optimization. Springer. |
| 2010 | Neumann, F., & Witt, C. (2010). Bioinspired Computation in Combinatorial Optimization. Springer. DOI |
| 2010 | Neumann, F., & Witt, C. (2010). Bioinspired computation in combinatorial optimization : algorithms and their computational complexity. Berlin: Springer. DOI |
| Year | Citation |
|---|---|
| 2022 | Goel, D., Ward-Graham, M. H., Neumann, A., Neumann, F., Nguyen, H., & Guo, M. (2022). Defending active directory by combining neural network based dynamic program and evolutionary diversity optimisation.. Poster session presented at the meeting of GECCO. ACM. |
| 2020 | Neumann, A., & Neumann, F. (2020). Evolutionary computation for digital art. Poster session presented at the meeting of Gecco 2020 Companion Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. ACM. DOI Scopus1 |
| 2020 | Bossek, J., Neumann, A., & Neumann, F. (2020). Evolutionary Diversity Optimisation. Poster session presented at the meeting of Parallel Problem Solving from Nature, PPSN 2020. |
| 2019 | Neumann, A., & Neumann, F. (2019). Evolutionary computation for digital art. Poster session presented at the meeting of Abstracts of the Genetic and Evolutionary Computation Conference Companion (GECCO 2019). Prague, The Czech Republic: Association for Computing Machinery (ACM). DOI Scopus1 WoS1 |
| 2018 | Neumann, A., & Neumann, F. (2018). Evolutionary computation for digital art. Poster session presented at the meeting of Abstracts of the Genetic and Evolutionary Computation Conference Companion (GECCO 2018). Kyoto, Japan: Association for Computing Machinery. DOI Scopus2 |
| 2016 | Friedrich, T., Kötzing, T., Krejca, M. S., & Sutton, A. M. (2016). The Benefit of Recombination in Noisy Evolutionary Search.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Friedrich, T., Kötzing, T., Quinzan, F., & Sutton, A. M. (2016). Ant Colony Optimization Beats Resampling on Noisy Functions.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Colmenar, J. M., Winkler, S. M., Kronberger, G., Maqueda, E., Botella, M., & Hidalgo, J. I. (2016). Predicting Glycemia in Diabetic Patients By Evolutionary Computation and Continuous Glucose Monitoring.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Duarte, M., Costa, V., Gomes, J. C., Rodrigues, T., Silva, F., Oliveira, S. M., & Christensen, A. L. (2016). Unleashing the Potential of Evolutionary Swarm Robotics in the Real World.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Kheng, C. W., Ku, D. C., Ng, H. -F., Khattab, M. A. H. M., & Chong, S. Y. (2016). Curvature Flight Path for Particle Swarm Optimisation.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Martins, M. S., Delgado, M. R. D. B. D. S., Santana, R., Lüders, R., Gonçalves, R. A., & Almeida, C. P. D. (2016). HMOBEDA: Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Guervós, J. J. M., Castillo, P. A., García-Sánchez, P., Cuevas, P. D. L., Rico, N., & Valdez, M. G. (2016). Performance for the Masses: Experiments with A Web Based Architecture to Harness Volunteer Resources for Low Cost Distributed Evolutionary Computation.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Paula, L. C. D., Soares, A. D. S., Lima, T. W. D., Filho, A. R., & Coelho, C. J. (2016). Variable Selection for Multivariate Calibration in Chemometrics: A Real-World Application with Building Blocks Disruption Problem.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Dang, D. -C., Friedrich, T., Kötzing, T., Krejca, M. S., Lehre, P. K., Oliveto, P. S., . . . Sutton, A. M. (2016). Escaping Local Optima with Diversity Mechanisms and Crossover.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Fernando, C., Banarse, D., Reynolds, M., Besse, F., Pfau, D., Jaderberg, M., . . . Wierstra, D. (2016). Convolution by Evolution: Differentiable Pattern Producing Networks.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Larson, A., Bernatskiy, A., Cappelle, C., Livingston, K. R., Livingston, N., Jr, J. H. L., . . . Bongard, J. C. (2016). Recombination Hotspots Promote the Evolvability of Modular Systems.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Urselmann, M., Foussette, C., Janus, T., Tlatlik, S., Gottschalk, A., Emmerich, M. T., . . . Bäck, T. (2016). Selection of a DFO Method for the Efficient Solution of Continuous Constrained Sub-Problems within a Memetic Algorithm for Chemical Process Synthesis.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Scott, E. O., & De Jong, K. A. (2016). Evaluation-time bias in quasi-generational and steady-state asynchronous evolutionary algorithms. Poster session presented at the meeting of Gecco 2016 Proceedings of the 2016 Genetic and Evolutionary Computation Conference. Denver, CO: ASSOC COMPUTING MACHINERY. DOI Scopus11 WoS10 |
| 2016 | Shim, Y., Auerbach, J. E., & Husbands, P. (2016). Darwinian Dynamics of Embodied Chaotic Exploration.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Urbanowicz, R. J., Browne, W. N., & Kuber, K. (2016). Hands-on Workshop on Learning Classifier Systems.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Pugh, J. K., Soros, L. B., & Stanley, K. O. (2016). An Extended Study of Quality Diversity Algorithms.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Smith, S. L., Cagnoni, S., & Patton, R. M. (2016). MedGEC'16 Chairs' Welcome.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Tarapore, D., Clune, J., Cully, A., & Mouret, J. -B. (2016). How do Different Encodings Influence the Performance of the MAP-Elites Algorithm?. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Woodward, J. R., Johnson, C. G., & Brownlee, A. E. (2016). Connecting Automatic Parameter Tuning, Genetic Programming as a Hyper-heuristic, and Genetic Improvement Programming.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Toosi, F. G., Nikolov, N. S., & Eaton, M. (2016). A GA-Inspired Approach to the Reduction of Edge Crossings in Force-Directed Layouts.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Wilson, D., Cussat-Blanc, S., & Luga, H. (2016). The Evolution of Artificial Neurogenesis.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Zuin, G. L., Macedo, Y. P., Chaimowicz, L., & Pappa, G. L. (2016). Discovering Combos in Fighting Games with Evolutionary Algorithms.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Zutty, J., Long, D., & Rohling, G. (2016). Increasing the Throughput of Expensive Evaluations Through a Vector Based Genetic Programming Framework.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Alvarez, I. M., Browne, W. N., & Zhang, M. (2016). Human-inspired Scaling in Learning Classifier Systems: Case Study on the n-bit Multiplexer Problem Set.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Andersson, M., Bandaru, S., & Ng, A. H. (2016). Tuning of Multiple Parameter Sets in Evolutionary Algorithms.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Arrieta, A., Wang, S., Sagardui, G., & Etxeberria, L. (2016). Test Case Prioritization of Configurable Cyber-Physical Systems with Weight-Based Search Algorithms.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Arnaldo, I., Hemberg, E., & O'Reilly, U. -M. (2016). Multi-Line Batch Scheduling by Similarity.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Asafuddoula, M., Singh, H. K., & Ray, T. (2016). A CUDA Implementation of an Improved Decomposition Based Evolutionary Algorithm for Multi-Objective Optimization.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Basseur, M., Derbel, B., Goëffon, A., & Liefooghe, A. (2016). Experiments on Greedy and Local Search Heuristics for ddimensional Hypervolume Subset Selection.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Brotánková, J., Urli, T., & Kilby, P. (2016). Planning Habitat Restoration with Genetic Algorithms.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Bulanova, N., Buzdalova, A., & Buzdalov, M. (2016). Fitness-Dependent Hybridization of Clonal Selection Algorithm and Random Local Search.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Chen, Q., Xue, B., Shang, L., & Zhang, M. (2016). Improving generalisation of genetic programming for symbolic regression with structural risk minimisation. Poster session presented at the meeting of Gecco 2016 Proceedings of the 2016 Genetic and Evolutionary Computation Conference. ACM. DOI Scopus22 |
| 2016 | Contreras, S. F., Cortés, C. A., & Guzmán, M. A. (2016). Bio-inspired Multi-objective Optimization Design of a Highly Efficient Squirrel Cage Induction Motor.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Cruz, C., Karakiewicz, J., & Kirley, M. (2016). A Morphogenetic Design Strategy Using a Composite CA Model.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Doerr, B., Doerr, C., & Yang, J. (2016). Optimal Parameter Choices via Precise Black-Box Analysis.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Fernandes, C. M., Guervós, J. J. M., & Rosa, A. C. (2016). Asynchronous Steady State Particle Swarm.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Fernandez, S., Stützle, T., & Pellicer, P. V. (2016). IAM 2016 Chairs' Welcome & Organization.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Gilan, S. S., Goyal, N., & Dilkina, B. (2016). Active Learning in Multi-objective Evolutionary Algorithms for Sustainable Building Design.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Ha, S., Lee, S., & Moon, B. -R. (2016). Inspecting the Latent Space of Stock Market Data with Genetic Programming.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Helmuth, T., McPhee, N. F., & Spector, L. (2016). The Impact of Hyperselection on Lexicase Selection.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Helmuth, T., McPhee, N. F., & Spector, L. (2016). Effects of Lexicase and Tournament Selection on Diversity Recovery and Maintenance.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Cramer, S., Kampouridis, M., & Freitas, A. A. (2016). A Genetic Decomposition Algorithm for Predicting Rainfall within Financial Weather Derivatives.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Huizinga, J., Mouret, J. -B., & Clune, J. (2016). Does Aligning Phenotypic and Genotypic Modularity Improve the Evolution of Neural Networks?. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Kamizono, M., Shimomura, K., Tajiri, M., & Ono, S. (2016). Two-Dimensional Barcode Decoration Using Module-wise Non-systematic Coding and Cooperative Evolution by User and System.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Kerschke, P., Preuss, M., Wessing, S., & Trautmann, H. (2016). Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Ge, Y. -F., Yu, W. -J., & Zhang, J. (2016). Diversity-Based Multi-Population Differential Evolution for Large-Scale Optimization.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Greensmith, J., Jackson, A. M., & Spendlove, I. (2016). Exploiting the Plasticity of Primary and Secondary Response Mechanisms in Artificial Immune Systems.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Martínez, S. Z., Moraglio, A., Aguirre, H. E., & Tanaka, K. (2016). Geometric Particle Swarm Optimization for Multi-objective Optimization Using Decomposition.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Salomon, S., Purshouse, R. C., Giagkiozis, I., & Fleming, P. J. (2016). A Toolkit for Generating Scalable Stochastic Multiobjective Test Problems.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Abdolmaleki, A., Lau, N., Reis, L. P., & Neumann, G. (2016). Contextual Stochastic Search.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Doncieux, S., Auerbach, J. E., Duro, R. J., & Vladar, H. P. D. (2016). Evolution in Cognition 2016 Chairs' Welcome.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Espinoza-Nevárez, D., Ortiz-Bayliss, J. C., Terashima-Marín, H., & Gatica, G. (2016). Selection and Generation Hyper-heuristics for Solving the Vehicle Routing Problem with Time Windows.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Gómez, R. H., Coello, C. A. C., & Torres, E. A. (2016). A Multi-Objective Evolutionary Algorithm based on Parallel Coordinates.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Kenny, A., Li, X., Qin, A. K., & Ernst, A. T. (2016). A Population-based Local Search Technique with Random Descent and Jump for the Steiner Tree Problem in Graphs.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Mihoc, T. D., Lung, R. I., Gaskó, N., & Suciu, M. (2016). Approximation of (k, t)-robust Equilibria.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Roy, P. C., Islam, M. M., & Deb, K. (2016). Best Order Sort: A New Algorithm to Non-dominated Sorting for Evolutionary Multi-objective Optimization.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Santos, V. L. A., Arroyo, J. E. C., & Carvalho, T. F. M. (2016). Iterated Local Search Based Heuristic for Scheduling Jobs on Unrelated Parallel Machines with Machine Deterioration Effect.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Steenkiste, S. V., Koutník, J., Driessens, K., & Schmidhuber, J. (2016). A Wavelet-based Encoding for Neuroevolution.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Bartoli, A., Lorenzo, A. D., Medvet, E., & Tarlao, F. (2016). On the Automatic Construction of Regular Expressions from Examples (GP vs. Humans 1-0).. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Bergé, P., Guiban, K. L., Rimmel, A., & Tomasik, J. (2016). Search Space Exploration and an Optimization Criterion for Hard Design Problems.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Duarte, M., Gomes, J. C., Oliveira, S. M., & Christensen, A. L. (2016). EvoRBC: Evolutionary Repertoire-based Control for Robots with Arbitrary Locomotion Complexity.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Ellefsen, K. O., Lepikson, H. A., & Albiez, J. C. (2016). Planning Inspection Paths through Evolutionary Multi-objective Optimization.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Benítez, C. M. V., Parpinelli, R. S., & Lopes, H. S. (2016). An Ecologically-inspired Parallel Approach Applied to the Protein Structure Reconstruction from Contact Maps.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Garbelini, J. C., Kashiwabara, A. Y., & Sanches, D. S. (2016). Discovery Motifs by Evolutionary Computation.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Labidi, M. K., Diarrassouba, I., Mahjoub, A. R., & Omrane, A. (2016). A Parallel Hybrid Genetic Algorithm for the k-Edge-Connected Hop-Constrained Network Design Problem.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Mariani, T., Guizzo, G., Vergilio, S. R., & Pozo, A. T. (2016). Grammatical Evolution for the Multi-Objective Integration and Test Order Problem.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Martí, L., Tchango, A. F., Navarro, L., & Schoenauer, M. (2016). VorAIS: A Multi-Objective Voronoi Diagram-based Artificial Immune System.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Medernach, D., Fitzgerald, J., Azad, R. M. A., & Ryan, C. (2016). A New Wave: A Dynamic Approach to Genetic Programming.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Nielsen, S. S., Torres, C. F., Danoy, G., & Bouvry, P. (2016). Tackling the IFP Problem with the Preference-Based Genetic Algorithm.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Pagán, J., Risco-Martín, J. L., Moya, J. M., & Ayala, J. L. (2016). Grammatical Evolutionary Techniques for Prompt Migraine Prediction.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Perez-Carabaza, S., Besada-Portas, E., Orozco, J. A. L., & Cruz, J. M. D. L. (2016). A Real World Multi-UAV Evolutionary Planner for Minimum Time Target Detection.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Rocha, G. K., Custódio, F. L., Barbosa, H. J., & Dardenne, L. E. (2016). Using Crowding-Distance in a Multiobjective Genetic Algorithm for Protein Structure Prediction.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Smith, R. J., Zincir-Heywood, A. N., Heywood, M. I., & Jacobs, J. T. (2016). Initiating a Moving Target Network Defense with a Real-time Neuro-evolutionary Detector.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Sosa-Ascencio, A., Terashima-Marín, H., Ortiz-Bayliss, J. C., & Conant-Pablos, S. E. (2016). Grammar-based Selection Hyper-heuristics for Solving Irregular Bin Packing Problems.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Sotto, L. F. D. P., Coelho, R. C., & Melo, V. V. D. (2016). Classification of Cardiac Arrhythmia by Random Forests with Features Constructed by Kaizen Programming with Linear Genetic Programming.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Suciu, M., Lung, R. I., & Gaskó, N. (2016). Game theory, Extremal optimization, and Community Structure Detection in Complex Networks.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Tran, C. T., Zhang, M., Andreae, P., & Xue, B. (2016). Directly Constructing Multiple Features for Classification with Missing Data using Genetic Programming with Interval Functions.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Khadka, S., Tumer, K., Colby, M. K., Tucker, D., Pezzini, P., & Bryden, K. M. (2016). Neuroevolution of a Hybrid Power Plant Simulator.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Abdolmaleki, A., Lioutikov, R., Lau, N., Reis, L. P., Peters, J., & Neumann, G. (2016). Model-Based Relative Entropy Stochastic Search.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Bevilacqua, V., Brunetti, A., Triggiani, M., Magaletti, D., Telegrafo, M., & Moschetta, M. (2016). An Optimized Feed-forward Artificial Neural Network Topology to Support Radiologists in Breast Lesions Classification.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Tatsumi, T., Komine, T., Nakata, M., Sato, H., Kovacs, T., & Takadama, K. (2016). Variance-based Learning Classifier System without Convergence of Reward Estimation.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Larsen, S. J., Alkærsig, F. G., Ditzel, H. J., Jurisica, I., Alcaraz, N., & Baumbach, J. (2016). A Simulated Annealing Algorithm for Maximum Common Edge Subgraph Detection in Biological Networks.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Liu, X., Li, F., Ding, Y., Wang, L., & Hao, K. (2016). Mechanical Modeling with Particle Swarm Optimization Algorithm for Braided Bicomponent Ureteral Stent.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Lynch, D., Fenton, M., Kucera, S., Claussen, H., & O'Neill, M. (2016). Evolutionary Learning of Scheduling Heuristics for Heterogeneous Wireless Communications Networks.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Guervós, J. J. M., Castillo, P. A., García-Sánchez, P., Cuevas, P. D. L., & Valdez, M. G. (2016). NodIO: A Framework and Architecture for Pool-based Evolutionary Computation.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Osaba, E., López-García, P., Masegosa, A. D., Onieva, E., Landaluce, H., & Perallos, A. (2016). TIMON Project: Description and Preliminary Tests for Traffic Prediction Using Evolutionary Techniques.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Kordmahalleh, M. M., Sefidmazgi, M. G., & Homaifar, A. (2016). A Sparse Recurrent Neural Network for Trajectory Prediction of Atlantic Hurricanes.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Sorrosal, G., Borges, C. E., Holeña, M., Macarulla, A. M., Andonegui, C. M., & Alonso-Vicario, A. (2016). Evolutionary Dynamic Optimization of Control Trajectories for the Catalytic Transformation of the Bioethanol-To-Olefins Process using Neural Networks.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Ahrari, A., Lei, H., Sharif, M. A., Deb, K., & Tan, X. (2016). Optimum Design of Artificial Lateral Line Systems for Object Tracking under Uncertain Conditions.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Scheibenpflug, A., Karder, J., Schaller, S., Wagner, S., & Affenzeller, M. (2016). Evolutionary Procedural 2D Map Generation using Novelty Search.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Szubert, M., Kodali, A., Ganguly, S., Das, K., & Bongard, J. C. (2016). Reducing Antagonism between Behavioral Diversity and Fitness in Semantic Genetic Programming.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Vallejo, M., Cosgrove, J., Alty, J. E., Smith, S. L., Corne, D. W., & Lones, M. A. (2016). Using Multiobjective Evolutionary Algorithms to Understand Parkinson's Disease.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Auger, A., Brockhoff, D., Hansen, N., Tusar, D., Tusar, T., & Wagner, T. (2016). GECCO'16 Black-Box Optimization Benchmarking Workshop (BBOB-2016): Workshop Chairs' Welcome Message.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Sanches, D. S., Jr, J. B. A. L., & Delbem, A. C. (2016). Multiobjective Discrete Differential Evolution for Service Restoration in Energy Distribution Systems.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Badr, G., Hosny, M. I., Bintayyash, N., Albilali, E., & Marie-Sainte, S. L. (2016). BeamGA Median: A Hybrid Heuristic Search Framework.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Butcher, S., Strasser, S., Hoole, J., Demeo, B., & Sheppard, J. W. (2016). Relaxing Consensus in Distributed Factored Evolutionary Algorithms.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Cumbo, K. C., Heck, S., Tanimoto, I., DeVault, T., Heckendorn, R. B., & Soule, T. (2016). Bee-Inspired Landmark Recognition in Robotic Navigation.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Derbel, B., Liefooghe, A., Zhang, Q., Aguirre, H. E., & Tanaka, K. (2016). Local Search Move Strategies within MOEA/D.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Fernandez, S., Valledor, P., Díaz, D., Malatsetxebarria, E., & Iglesias, M. (2016). Criticality of Response Time in the usage of Metaheuristics in Industry.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Salgado, R., Prieto, A., Bellas, F., Calvo-Varela, L., & Duro, R. J. (2016). Neuroevolutionary Motivational Engine for Autonomous Robots.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Stolfi, D. H., Armas, R., Alba, E., Aguirre, H. E., & Tanaka, K. (2016). Fine Tuning of Traffic in our Cities with Smart Panels: The Quito City Case Study.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Vallejo, M., Cosgrove, J., Alty, J. E., Jamieson, S., Smith, S. L., Corne, D. W., & Lones, M. A. (2016). A Multi-Objective Approach to Predicting Motor and Cognitive Deficit in Parkinson's Disease Patients.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Vladar, H. P. D., Fedor, A., Szilágyi, A., Zachar, I., & Szathmáry, E. (2016). An Attractor Network-Based Model with Darwinian Dynamics.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Wang, Y., Qian, Y., Li, Y., Gong, M., & Banzhaf, W. (2016). Artificial Multi-Bee-Colony Algorithm for k-Nearest-Neighbor Fields Search.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Colby, M. K., Yliniemi, L. M., Pezzini, P., Tucker, D., Bryden, K. M., & Tumer, K. (2016). Multiobjective Neuroevolutionary Control for a Fuel Cell Turbine Hybrid Energy System.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Paula, L. C. D., Soares, A. D. S., Lima, T. W. D., & Coelho, C. J. (2016). Feature Selection using Genetic Algorithm: An Analysis of the Bias-Property for One-Point Crossover.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Khalifa, A., Liebana, D. P., Lucas, S. M., & Togelius, J. (2016). General Video Game Level Generation.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Stefano, C. D., Fontanella, F., & Freca, A. S. D. (2016). A Novel GA-based Feature Selection Approach for High Dimensional Data.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Liu, X. F., Zhan, Z. -H., Lin, J. -H., & Zhang, J. (2016). Parallel Differential Evolution Based on Distributed Cloud Computing Resources for Power Electronic Circuit Optimization.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Duro, R. J., Becerra, J. A., Monroy, J., & Caamaño, P. (2016). Considering Memory Networks in the LTM Structure of the Multilevel Darwinist Brain.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Volz, V., Rudolph, G., & Naujoks, B. (2016). Demonstrating the Feasibility of Automatic Game Balancing.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Plachkov, A., Abielmona, R. S., Harb, M., Falcon, R., Inkpen, D., Groza, V., & Petriu, E. M. (2016). Automatic Course of Action Generation using Soft Data for Maritime Domain Awareness.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Marmion, M. -E., Aguirre, H. E., Dhaenens, C., Jourdan, L., & Tanaka, K. (2016). Multi-objective Neutral Neighbors': What could be the definition(s)?. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Langdon, W. B., Vilella, A., Lam, B. Y. H., Petke, J., & Harman, M. (2016). Benchmarking Genetically Improved BarraCUDA on Epigenetic Methylation NGS datasets and nVidia GPUs.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Auger, A., Brockhoff, D., Hansen, N., Tusar, D., Tusar, T., & Wagner, T. (2016). The Impact of Search Volume on the Performance of RANDOMSEARCH on the Bi-objective BBOB-2016 Test Suite.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Auger, A., Brockhoff, D., Hansen, N., Tusar, D., Tusar, T., & Wagner, T. (2016). Benchmarking MATLAB's gamultiobj (NSGA-II) on the Bi-objective BBOB-2016 Test Suite.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Spector, L., McPhee, N. F., Helmuth, T., Casale, M. M., & Oks, J. (2016). Evolution Evolves with Autoconstruction.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Rahat, A. A. -A., Everson, R. M., Fieldsend, J. E., Jin, Y., & Wang, H. (2016). Surrogate-Assisted Evolutionary Optimisation (SAEOpt'16) Chairs' Welcome & Organization.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Panichella, A., Alexandru, C. V., Panichella, S., Bacchelli, A., & Gall, H. C. (2016). A Search-based Training Algorithm for Cost-aware Defect Prediction.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | McPhee, N. F., Casale, M. M., Finzel, M., Helmuth, T., & Spector, L. (2016). Visualizing Genetic Programming Ancestries.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Auger, A., Brockhoff, D., Hansen, N., Tusar, D., Tusar, T., & Wagner, T. (2016). Benchmarking RM-MEDA on the Bi-objective BBOB-2016 Test Suite.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Auger, A., Brockhoff, D., Hansen, N., Tusar, D., Tusar, T., & Wagner, T. (2016). The Impact of Variation Operators on the Performance of SMS-EMOA on the Bi-objective BBOB-2016 Test Suite.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2016 | Leclerc, G., Auerbach, J. E., Iacca, G., & Floreano, D. (2016). The Seamless Peer and Cloud Evolution Framework.. Poster session presented at the meeting of GECCO. ACM. |
| 2016 | Auger, A., Brockhoff, D., Hansen, N., Tusar, D., Tusar, T., & Wagner, T. (2016). Benchmarking the Pure Random Search on the Bi-objective BBOB-2016 Testbed.. Poster session presented at the meeting of GECCO (Companion). ACM. |
| 2012 | Neumann, F., & Witt, C. (2012). Bioinspired computation in combinatorial optimization: algorithms and their computational complexity. Poster session presented at the meeting of GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation. Philadelphia, U.S.A.: ACM. DOI Scopus12 WoS9 |
| 2011 | Friedrich, T., & Neumann, F. (2011). Foundations of evolutionary multi-objective optimization. Poster session presented at the meeting of Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication. Dublin, Ireland: ACM. DOI |
| 2011 | Jansen, T., & Neumann, F. (2011). Computational complexity and evolutionary computation. Poster session presented at the meeting of Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication. Dublin, Ireland: ACM. DOI |
| Year | Citation |
|---|---|
| 2017 | Hoeltgen, L., Mainberger, M., Hoffmann, S., Weickert, J., Tang, C. H., Setzer, S., . . . Doerr, B. (2017). Optimizing spatial and tonal data for PDE-based inpainting. Scopus13 |
| 2016 | Pourhassan, M., Shi, F., & Neumann, F. (2016). Parameterized analysis of multi-objective evolutionary algorithms and the weighted vertex cover problem. SPRINGER INTERNATIONAL PUBLISHING AG. DOI Scopus12 WoS8 |
| 2014 | Polyakovskiy, S., Berghammer, R., & Neumann, F. (2014). Solving Hard Control Problems in Voting Systems via Integer Programming.. |
| 2013 | Friedrich, T., Neumann, F., & Thyssen, C. (2013). Multiplicative Approximations, Optimal Hypervolume Distributions, and the Choice of the Reference Point.. |
| 2012 | Doerr, B., Johannsen, D., Kötzing, T., Neumann, F., & Theile, M. (2012). More Effective Crossover Operators for the All-Pairs Shortest Path Problem. |
| 2011 | Wagner, M., & Neumann, F. (2011). Computational Complexity Results for Genetic Programming and the Sorting Problem. |
| Year | Citation |
|---|---|
| 2019 | Xie, Y., Harper, O., Assimi, H., Neumann, A., & Neumann, F. (2019). Evolutionary algorithms for the chance-constrained knapsack problem.. ACM. |
| 2019 | Neumann, A., Neumann, F., & Friedrich, T. (2019). Quasi-random Image Transition and Animation.. |
| 2017 | Neumann, A., Neumann, F., & Friedrich, T. (2017). Quasi-random Agents for Image Transition and Animation.. |
| 2016 | Neumann, A., Alexander, B., & Neumann, F. (2016). Evolutionary Image Transition Based on Theoretical Insights of Random Processes.. |
| Year | Citation |
|---|---|
| 2025 | Pan, S., Patel, Y. J., Neumann, A., Neumann, F., Bäck, T., & Wang, H. (2025). Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms. |
| 2024 | Santoni, M. L., Raponi, E., Neumann, A., Neumann, F., Preuss, M., & Doerr, C. (2024). Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization. |
| 2024 | Antipov, D., Neumann, A., Neumann, F., & Sutton, A. M. (2024). Runtime Analysis of Evolutionary Diversity Optimization on the Multi-objective (LeadingOnes, TrailingZeros) Problem.. |
| 2024 | Yan, X., Neumann, A., & Neumann, F. (2024). Sampling-based Pareto Optimization for Chance-constrained Monotone Submodular Problems.. |
| 2024 | Doerr, B., Knowles, J., Neumann, A., & Neumann, F. (2024). A Block-Coordinate Descent EMO Algorithm: Theoretical and Empirical Analysis. |
| 2024 | Yan, X., Neumann, A., & Neumann, F. (2024). Sliding Window Bi-Objective Evolutionary Algorithms for Optimizing Chance-Constrained Monotone Submodular Functions.. |
| 2024 | Neumann, F., & Rudolph, G. (2024). Archive-based Single-Objective Evolutionary Algorithms for Submodular Optimization.. |
| 2024 | Opris, A., Dang, D. -C., Neumann, F., & Sudholt, D. (2024). Runtime Analyses of NSGA-III on Many-Objective Problems.. |
| 2024 | Neumann, F., & Witt, C. (2024). Sliding Window 3-Objective Pareto Optimization for Problems with Chance Constraints.. |
| 2024 | Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2024). Evolutionary Multi-Objective Diversity Optimization.. |
| 2024 | Pathiranage, I. H., Neumann, F., Antipov, D., & Neumann, A. (2024). Using 3-Objective Evolutionary Algorithms for the Dynamic Chance Constrained Knapsack Problem.. |
| 2024 | Antipov, D., Neumann, A., & Neumann, F. (2024). Local Optima in Diversity Optimization: Non-trivial Offspring Population is Essential.. |
| 2024 | Ahouei, S. S., Nobel, J. D., Neumann, A., Bäck, T., & Neumann, F. (2024). Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem. |
| 2024 | Harder, J. G., Neumann, A., & Neumann, F. (2024). Analysis of Evolutionary Diversity Optimisation for the Maximum Matching Problem.. |
| 2023 | Guo, M., Li, J., Neumann, A., Neumann, F., & Nguyen, H. (2023). Limited Query Graph Connectivity Test. |
| 2023 | Friedrich, T., Kötzing, T., Neumann, A., Neumann, F., & Radhakrishnan, A. (2023). Analysis of the (1+1) EA on LeadingOnes with Constraints.. |
| 2023 | Ye, F., Neumann, F., Nobel, J. D., Neumann, A., & Bäck, T. (2023). Towards Self-adaptive Mutation in Evolutionary Multi-Objective Algorithms. |
| 2023 | Ghasemi, Z., Neshat, M., Aldrich, C., Karageorgos, J., Zanin, M., Neumann, F., & Chen, L. (2023). A Hybrid Intelligent Framework for Maximising SAG Mill Throughput: An Integration of Expert Knowledge, Machine Learning and Evolutionary Algorithms for Parameter Optimisation.. |
| 2023 | Antipov, D., Neumann, A., & Neumann, F. (2023). Rigorous Runtime Analysis of Diversity Optimization with GSEMO on OneMinMax.. |
| 2023 | Yan, X., Do, A. V., Shi, F., Qin, X., & Neumann, F. (2023). Optimizing Chance-Constrained Submodular Problems with Variable Uncertainties.. |
| 2023 | Goel, D., Neumann, A., Neumann, F., Nguyen, H., & Guo, M. (2023). Evolving Reinforcement Learning Environment to Minimize Learner's Achievable Reward: An Application on Hardening Active Directory Systems.. |
| 2023 | Guo, M., Li, J., Neumann, A., Neumann, F., & Nguyen, H. (2023). Limited Query Graph Connectivity Test.. |
| 2023 | Do, A. V., Neumann, A., Neumann, F., & Sutton, A. M. (2023). Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems.. |
| 2023 | Do, A. V., Guo, M., Neumann, A., & Neumann, F. (2023). Diverse Approximations for Monotone Submodular Maximization Problems with a Matroid Constraint.. |
| 2023 | Zoltai, G., Xie, Y., & Neumann, F. (2023). A Study of Fitness Gains in Evolving Finite State Machines.. |
| 2023 | Neumann, F., Neumann, A., Qian, C., Do, A. V., Nobel, J. D., Vermetten, D., . . . Bäck, T. (2023). Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler.. |
| 2022 | Guo, M., Ward, M., Neumann, A., Neumann, F., & Nguyen, H. (2022). Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs.. |
| 2022 | Shi, F., Yan, X., & Neumann, F. (2022). Runtime Performance of Evolutionary Algorithms for the Chance-constrained Makespan Scheduling Problem.. |
- NHMRC Ideas Grant "Optimising time use for health and wellbeing", National Health and Medical Research Council, 2020-2023 (led by Dorothea Dumuid at the University of South Australia, several investigators).
- ARC Discovery Project "Evolutionary diversity optimisation", Australian Research Council, 2019-2021 (with Tobias Friedrich).
- Humboldt Fellowship for Experienced Researchers, Alexander von Humboldt Foundation, 2019-2021.
- ARC Industrial Transformation Training Centre for Integrated Operations for Complex Resources, Australian Research Council, 2019-2023 (several chief investigators and industry partners).
- Project "Detection and classification of malicious virtual grassroots influence campaigns in social media", Australia-Germany Joint Research Co-operation Scheme, 2020-2021 (with Lewis Mitchell, Christian Grimme, Mewish Nasim, Derek Weber, Dennis Assenmacher, Lena Adam, Heike Trautmann).
- Research Consortium – Unlocking Complex Resources through Lean Processing, Research Consortia Program, State Government of South Australia, 2017-2021 (several chief investigators and industry partners).
- ARC Discovery Project "Bio-inspired Computing for Problems with Dynamically Changing Constraints", Australian Research Council, 2016-2018 (with Zbigniew Michalewicz, Tobias Friedrich, Marc Schoenauer)
- Project "Modelling and optimisation of submerged buoys for improved ocean wave energy production", Interdisciplinary Research Fund, The University of Adelaide, 2015 (with Markus Wagner, Boyin Ding, Benjamin Cazzolato, Maziar Arjomandi).
- ARC Discovery Project "Parameterised analysis of bio-inspired computing - from theory to high performing algorithms", Australian Research Council, 2014-2016 (with Tobias Friedrich)
- ARC Discovery Project "Advanced planning systems for vertically integrated supply chain management", Australian Research Council, 2013-2015 (with Zbigniew Michalewicz and Adam Ghandar)
- Project "Exploring the evolutionary diversity of Australia's marine snakes to develop a bio-mimetic sea snake robot", Interdisciplinary Research Fund, The University of Adelaide, 2013-2014 (with Lei Chen, Kate Sanders, Amy Watson, Gustavo Carneiro, Brett Goodman, Marc Jones)
- Evolutionary Computation, semester 2, 2018
- Grand Challenges in Computer Science, semester 2, 2017
- Evolutionary Computation, semester 1, 2017
- Mining Big Data, semester 1, 2017.
- Evolutionary Computation, semester 2, 2016
- Mining Big Data, semester 1, 2015.
- Mining Big Data, semester 1, 2014.
- Evolutionary Computation, semester 2, 2013.
- Advanced Algorithms, semester 1, 2013.
- Evolutionary Computation, semester 2, 2012.
- Algorithm and Data Structure Analysis, semester 1, 2012.
- Evolutionary Computation, semester 2, 2011.
- Data Structures and Algorithms, semester 2, 2011.
- Data Structures and Algorithms, semester 1, 2011.
- Algorithms and Data Structures, winter semester, 2009/2010. (Saarland University, Germany)
| Date | Role | Research Topic | Program | Degree Type | Student Load | Student Name |
|---|---|---|---|---|---|---|
| 2025 | Principal Supervisor | Optimizing Multiple Travelling Thieves Problem (MTTP) for Perishable Items under Chance Deadlines Constraint using Metaheuristic Algorithms | Doctor of Philosophy | Doctorate | Full Time | Helen Angmalisang |
| 2025 | Principal Supervisor | Optimizing Multiple Travelling Thieves Problem (MTTP) for Perishable Items under Chance Deadlines Constraint using Metaheuristic Algorithms | Doctor of Philosophy | Doctorate | Full Time | Helen Yuliana Angmalisang |
| 2024 | Co-Supervisor | Leveraging Machine Learning Agents for Military Application | Doctor of Philosophy | Doctorate | Full Time | Mr Josh Dylan Francis |
| 2024 | Principal Supervisor | Multitasking evolutionary algorithms for combinatorial optimisation | Doctor of Philosophy | Doctorate | Full Time | Mr Liam Joshua Daly Wigney |
| 2024 | Co-Supervisor | Realisation of Deep Learning Algorithms and Computer Vision on Quantum Computers | Doctor of Philosophy | Doctorate | Full Time | Ms Fengyi Yang |
| 2024 | Co-Supervisor | Leveraging Machine Learning Agents for Military Application | Doctor of Philosophy | Doctorate | Full Time | Mr Josh Dylan Francis |
| 2024 | Co-Supervisor | Realisation of Deep Learning Algorithms and Computer Vision on Quantum Computers | Doctor of Philosophy | Doctorate | Full Time | Ms Fengyi Yang |
| 2024 | Principal Supervisor | Multitasking evolutionary algorithms for combinatorial optimisation | Doctor of Philosophy | Doctorate | Full Time | Mr Liam Joshua Daly Wigney |
| 2022 | Principal Supervisor | Evolutionary Algorithms for Solving Chance Constrained Combinatorial Optimization Problems | Doctor of Philosophy | Doctorate | Full Time | Miss Saba Sadeghi Ahouei |
| 2022 | Co-Supervisor | Bio-inspired Computing for Problems with Chance Constraints | Doctor of Philosophy | Doctorate | Full Time | Mrs Kokila Perera |
| 2022 | Principal Supervisor | Bio-inspired algorithms for stochastic multi-component problems | Doctor of Philosophy | Doctorate | Full Time | Mr Thilina Pathirage Don |
| 2022 | Co-Supervisor | Bio-inspired Computing for Problems with Chance Constraints | Doctor of Philosophy | Doctorate | Full Time | Mrs Kokila Perera |
| 2022 | Principal Supervisor | Evolutionary Algorithms for Solving Chance Constrained Combinatorial Optimization Problems | Doctor of Philosophy | Doctorate | Full Time | Miss Saba Sadeghi Ahouei |
| 2022 | Principal Supervisor | Bio-inspired algorithms for stochastic multi-component problems | Doctor of Philosophy | Doctorate | Full Time | Mr Thilina Pathirage Don |
| 2021 | Co-Supervisor | Maximising throughput through intelligent online sensing and health monitoring | Doctor of Philosophy | Doctorate | Part Time | Mr Zeqi Li |
| 2021 | Principal Supervisor | Is complexity an evolutionary response to selection change? | Master of Philosophy | Master | Part Time | Mr Gabor Zoltai |
| 2021 | Principal Supervisor | Is complexity an evolutionary response to selection change? | Master of Philosophy | Master | Full Time | Mr Gabor Zoltai |
| 2021 | Co-Supervisor | Maximising throughput through intelligent online sensing and health monitoring | Doctor of Philosophy | Doctorate | Full Time | Mr Zeqi Li |
| Date | Role | Research Topic | Program | Degree Type | Student Load | Student Name |
|---|---|---|---|---|---|---|
| 2023 - 2025 | Co-Supervisor | Maximising mill throughput using machine learning techniques and evolutionary algorithms | Doctor of Philosophy | Doctorate | Full Time | Mrs Zahra Ghasemi |
| 2022 - 2025 | Principal Supervisor | Theoretical and Experimental Analysis of Search Heuristics for Problems with Chance Constraints | Doctor of Philosophy | Doctorate | Full Time | Mr Xiankun Yan |
| 2021 - 2025 | Co-Supervisor | Rapid Updating of Resource Knowledge with Sensor Information Including Structures | Doctor of Philosophy | Doctorate | Full Time | Mr Sultan Abulkhair |
| 2020 - 2023 | Principal Supervisor | Evolutionary Diversity Optimisation for Combinatorial Problems | Doctor of Philosophy | Doctorate | Full Time | Mr Adel Nikfarjam |
| 2020 - 2024 | Principal Supervisor | Analysis of Search Heuristics for Diverse Solutions to Combinatorial Problems | Doctor of Philosophy | Doctorate | Full Time | Mr Viet Anh Do |
| 2019 - 2023 | Co-Supervisor | Mathematical Optimisation for Vision-based Problems in Space Domain Awareness |
Doctor of Philosophy | Doctorate | Full Time | Mr Chee Kheng Chng |
| 2018 - 2021 | Principal Supervisor | Bio-Inspired Computing for Chance-Constrained Combinatorial Optimisation Problems | Doctor of Philosophy | Doctorate | Full Time | Miss Yue Xie |
| 2018 - 2023 | Principal Supervisor | Application of Bio-inspired Algorithms to Selected Real-World Problems | Doctor of Philosophy | Doctorate | Part Time | Dr Hirad Assimi |
| 2017 - 2020 | Principal Supervisor | Bio-Inspired Computing for Complex and Dynamic Constrained Problems | Doctor of Philosophy | Doctorate | Full Time | Mr Vahid Roostapour |
| 2017 - 2020 | Principal Supervisor | Differential Evolution for Dynamic Constrained Continuous Optimisation | Doctor of Philosophy | Doctorate | Full Time | Mrs Maryam Hasani Shoreh |
| 2017 - 2022 | Principal Supervisor | Towards Exposing Coordinating Inauthentic Groups on Social Media | Doctor of Philosophy | Doctorate | Part Time | Mr Derek Christopher Weber |
| 2015 - 2017 | Principal Supervisor | Ambulatory Monitoring using Passive RFID Technology | Doctor of Philosophy | Doctorate | Full Time | Mr Asanga Wickramasinghe |
| 2015 - 2018 | Principal Supervisor | Exact and Heuristic Approaches for Multi-component Optimisation Problems | Doctor of Philosophy | Doctorate | Full Time | Mr Junhua Wu |
| 2013 - 2016 | Principal Supervisor | Diversity Optimization and Parameterized Analysis of Heuristic Search Methods for Combinatorial Optimization Problems | Doctor of Philosophy | Doctorate | Full Time | Dr Wanru Gao |
| 2013 - 2017 | Principal Supervisor | Parameterised Complexity Analysis of Evolutionary Algorithms for Combinatorial Optimization Problems | Doctor of Philosophy | Doctorate | Full Time | Dr Mojgan Pourhassan |
| 2012 - 2015 | Principal Supervisor | Parameterized Analysis of Bio-inspired Computation and the Traveling Salesperson Problem | Doctor of Philosophy | Doctorate | Full Time | Mrs Samadhi Nethmini Nallaperuma |
| 2012 - 2016 | Principal Supervisor | Feature-Based Selection of Bio-Inspired Algorithms for Constrained Continuous Optimisation | Doctor of Philosophy | Doctorate | Full Time | Mr Shayan Poursoltan |
| 2011 - 2015 | Co-Supervisor | Particle swarm optimization: Theoretical analysis, Modifications, and Applications to Constrained Optimization Problems | Doctor of Philosophy | Doctorate | Full Time | Mr Mohammadreza Bonyadi |
| 2011 - 2013 | Principal Supervisor | Theory and Applications of Bio-Inspired Algorithms | Doctor of Philosophy | Doctorate | Full Time | APrf Markus Wagner |
| Date | Institution | Department | Organisation Type | Country |
|---|---|---|---|---|
| 2018 - ongoing | Daitum | - | Business and professional | Australia |
| 2015 - ongoing | Complexica | - | Business and professional | Australia |
| 2015 - ongoing | Optimatics | - | Business and professional | Australia |
| 2014 - 2016 | Project SAGE Speed of Adaptation in Population Genetics and Evolutionary Computation | - | Scientific research | United Kingdom |
| Date | Role | Editorial Board Name | Institution | Country |
|---|---|---|---|---|
| 2017 - ongoing | Associate Editor | IEEE Transactions on Evolutionary Computation | - | - |
| 2014 - ongoing | Associate Editor | Evolutionary Computation | - | - |
