| Electric load forecasting methods: Tools for decision making H Hahn, S Meyer-Nieberg, S Pickl European journal of operational research 199 (3), 902-907, 2009 | 723 | 2009 |
| Self-adaptation in evolutionary algorithms S Meyer-Nieberg, HG Beyer Parameter setting in evolutionary algorithms, 47-75, 2007 | 274 | 2007 |
| Fuzzy prediction strategies for gene-environment networks–Fuzzy regression analysis for two-modal regulatory systems E Kropat, A Özmen, GW Weber, S Meyer-Nieberg, O Defterli RAIRO-Operations Research-Recherche Opérationnelle 50 (2), 413-435, 2016 | 51 | 2016 |
| Aerial vehicle search-path optimization: A novel method for emergency operations M Raap, S Meyer-Nieberg, S Pickl, M Zsifkovits Journal of Optimization Theory and Applications 172, 965-983, 2017 | 32 | 2017 |
| Self-adaptation in evolution strategies. S Meyer-Nieberg Dortmund University of Technology, 2007 | 29 | 2007 |
| Moving target search optimization–a literature review M Raap, M Preuß, S Meyer-Nieberg Computers & Operations Research 105, 132-140, 2019 | 25 | 2019 |
| On the analysis of self-adaptive recombination strategies: First results S Meyer-Nieberg, HG Beyer 2005 IEEE Congress on Evolutionary Computation 3, 2341-2348, 2005 | 24 | 2005 |
| Self-adaptation of evolution strategies under noisy fitness evaluations HG Beyer, S Meyer-Nieberg Genetic Programming and Evolvable Machines 7 (4), 295-328, 2006 | 23 | 2006 |
| A new approach for predicting the final outcome of evolution strategy optimization under noise HG Beyer, DV Arnold, S Meyer-Nieberg Genetic Programming and Evolvable Machines 6, 7-24, 2005 | 22 | 2005 |
| Collaborative risk management for national security and strategic foresight: Combining qualitative and quantitative operations research approaches M Dehmer, S Meyer-Nieberg, G Mihelcic, S Pickl, M Zsifkovits EURO Journal on Decision Processes 3 (3-4), 305-337, 2015 | 20 | 2015 |
| Evolving artificial neural networks for multi-objective tasks S Künzel, S Meyer-Nieberg Applications of Evolutionary Computation: 21st International Conference …, 2018 | 17 | 2018 |
| Intercepting a target with sensor swarms S Meyer-Nieberg, E Kropat, S Pickl, A Bordetsky 2013 46th Hawaii International Conference on System Sciences, 1222-1230, 2013 | 14 | 2013 |
| The dynamical systems approach—Progress measures and convergence properties S Meyer-Nieberg, HG Beyer Handbook of natural computing, 741-814, 2012 | 14 | 2012 |
| Time to dispense with the p-value in OR? Rationale and implications of the statement of the American Statistical Association (ASA) on p-values M Hofmann, S Meyer-Nieberg Central European Journal of Operations Research 26, 193-214, 2018 | 13 | 2018 |
| Why noise may be good: Additive noise on the sharp ridge S Meyer-Nieberg, HG Beyer Proceedings of the 10th annual conference on Genetic and evolutionary …, 2008 | 13 | 2008 |
| Mutative self-adaptation on the sharp and parabolic ridge S Meyer-Nieberg, HG Beyer Foundations of Genetic Algorithms: 9th International Workshop, FOGA 2007 …, 2007 | 13 | 2007 |
| Slime mold inspired evolving networks under uncertainty (SLIMO) E Kropat, S Meyer-Nieberg 2014 47th Hawaii International Conference on System Sciences, 1153-1161, 2014 | 10 | 2014 |
| Self-adaptation on the ridge function class: First results for the sharp ridge HG Beyer, S Meyer-Nieberg International Conference on Parallel Problem Solving from Nature, 72-81, 2006 | 10 | 2006 |
| Coping with opponents: multi-objective evolutionary neural networks for fighting games S Künzel, S Meyer-Nieberg Neural Computing and Applications 32 (17), 13885-13916, 2020 | 9 | 2020 |
| A multi-layered adaptive network approach for shortest path planning during critical operations in dynamically changing and uncertain environments E Kropat, S Meyer-Nieberg 2016 49th Hawaii International Conference on System Sciences (HICSS), 1369-1378, 2016 | 9 | 2016 |
