Publications

2024
Symbolic Regression

G. Kronberger, B. Burlacu, M. Kommenda, S. M. Winkler, M. Affenzeller - CRC Press

2024
The Inefficiency of Genetic Programming for Symbolic Regression

G. Kronberger, F. O. de Franca, H. Desmond, D. J. Bartlett, L. Kammerer - LNCS Vol. 15148, Parallel Problem Solving from Nature (PPSN XVIII), Springer

2024
Comparing Methods for Estimating Marginal Likelihood in Symbolic Regression

P. Leser, G. Bomarito, G. Kronberger, F. O. de Franca - GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference Companion, ACM

2024
A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming

Y. A. Radwan, G. Kronberger, S. Winkler - arXiv preprint, 2406.03585

2024
Population diversity and inheritance in genetic programming for symbolic regression

B. Burlacu, K. Yang, M. Affenzeller - Natural Computing, Vol. 23, pp. 531–566

2024
Population Dynamics in Genetic Programming for Dynamic Symbolic Regression

P. Fleck, B. Werth, M. Affenzeller - Applied Sciences, Vol. 14, Issue 2

2024
Surrogate-assisted multi-objective optimization via genetic programming based symbolic regression

K. Yang, M. Affenzeller - International Conference on Evolutionary Multi-Criterion Optimization, pp. 176-190

2024
A precise symbolic emulator of the linear matter power spectrum

D. J. Bartlett, L. Kammerer, G. Kronberger, H. Desmond, P. G. Ferreira, B. D. Wandelt, B. Burlacu, D. Alonso, M. Zennaro - Astronomy & Astrophysics 686 A209

2024
Learning Difference Equations with Structured Grammatical Evolution for Postprandial Glycaemia Prediction

D. Parra, D. Jödicke, J. M. Velasco, G. Kronberger, J. I. Hidalgo - IEEE Journal of Biomedical and Health Informatics

2024
Shape-constrained Symbolic Regression: Real-world Applications in Magnetization, Extrusion and Data Validation

C. Haider, F. O. de Franca, B. Burlacu, F. Bachinger, G. Kronberger, M. Affenzeller - Genetic Programming Theory and Practice XX, Springer

2024
Data Validation Utilizing Expert Knowledge and Shape Constraints

F. Bachinger, L. Ehrlinger, G. Kronberger, W. Wöß - Journal of Data and Information Quality, ACM

2023
Shape-constrained multi-objective genetic programming for symbolic regression

C. Haider, F. O. de Franca, B. Burlacu, G. Kronberger - Applied Soft Computing, Volume 132, 2023

2023
Prediction of microscopic residual stresses using genetic programming

L. Millán, G. Kronberger, R. Fernández, G. Bokuchava, P. Halodova, A. Sáez-Maderuelo, G. González-Doncel, J. I. Hidalgo - Applications in Engineering Sciences, 15, 100141, Elsevier

2023
Improving the Flexibility of Shape-Constrained Symbolic Regression with Extended Constraints

D. Piringer, S. Wagner, C. Haider, A. Fohler, S. Silber, M. Affenzellerr - Proceedings of the 18th International Conference on Computer Aided Systems Theory - EUROCAST 2022, Las Palmas de Gran Canaria, Spain (2022)

2023
Reducing Overparameterization of Symbolic Regression Models with Equality Saturation

F. O. de Franca, G. Kronberger - Proceedings of the Genetic and Evolutionary Conference (GECCO'24), pp. 1064 - 1072, ACM

2023
Extended melt‐conveying models for single‐screw extruders: Integrating domain knowledge into symbolic regression

C. Marschik, W. Roland, M. Kommenda - Polymer Engineering & Science, Vol. 63, Issue 11, pp. 3639-3656

2023
Evolutionary Algorithms for Segment Optimization in Vectorial GP

P.Fleck, S. M. Winkler, M. Kommenda, S. Silva, L. Vanneschi, M. Affenzeller - GECCO '23: Proceedings of the Companion Conference on Genetic and Evolutionary Computation, pp. 439-442

2023
Interpretable symbolic regression for data science: Analysis of the 2022 competition

F. O. de Franca, M. Virgolin, M. Kommenda, M. S. Majumder, M. Cranmer, G. Espada, L. Ingelse, A. Fonseca, M. Landajuela, B. Petersen, R. Glatt, N. Mundhenk, C. S. Lee, J. D. Hochhalter, D. L. Randall, P. Kamienny, H. Zhang, G. Dick, A. Simon, B. Burlacu, J. Kasak, M. Machado, C. Wilstrup, W. G. La Cava - arXiv preprint arXiv:2304.01117

2023
Vectorial Genetic Programming--Optimizing Segments for Feature Extraction

P. Fleck, S. M. Winkler, M. Kommenda, M. Affenzeller - arXiv preprint arXiv:2303.03200

2023
Symbolic regression in materials science: Discovering interatomic potentials from data

B. Burlacu, M. Kommenda, G. Kronberger, S. M. Winkler, M. Affenzeller - Genetic Programming Theory and Practice XIX, pp. 1-30, Springer

2023
Identification of Surrogate Models for the Prediction of Degrees of Freedom within a Tolerance Chain

H. Janout, T. Paier, C. Ringelhahn, M. Heckmann, A. Haghofer, G. Kronberger, S. M. Winkler - Procedia Computer Science, Vol. 217, pp. 796-805, Elsevier

2022
Simulation-based optimization of residential energy flows using white box modeling by genetic programming

K. Kefer, R. Hanghofer, P. Kefer, M. Stöger, B. Hofer, M. Affenzeller, S. M. Winkler - Energy and Buildings, Vol. 258, p. 111829

2022
Quantifying uncertainties of residuals in symbolic regression via kriging

K. Yang, M. Affenzeller - Procedia Computer Science, Vol. 200, pp. 954-961

2022
Genetic programming benchmarks: looking back and looking forward

J. McDermott, G. Kronberger, P. Orzechowski, L. Vanneschi, L. Manzoni, R. Kalkreuth, M. Castelli - SIGEVOlution, Vol. 15, Nr. 3, pp. 1-19, ACM

2022
Prediction Intervals and Confidence Regions for Symbolic Regression Models based on Likelihood Profiles

F. O. de Franca, G. Kronberger - arXiv preprint 2209.06454

2022
Identification of Non-Linear Dynamics of a Radio-Frequency Power Amplifier Circuit using Symbolic Regression

M. Steiger, H. G. Brachtendorf, G. Kronberger - 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), pp. 297 - 303, IEEE

2022
Steel phase kinetics modeling using symbolic regression

D. Piringer, B. Bloder, G. Kronberger - 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), pp. 327 - 330, IEEE

2022
Local Optimization Often is Ill-conditioned in Genetic Programming for Symbolic Regression

G. Kronberger - 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), pp. 304 - 310, IEEE

2022
Comparing optimistic and pessimistic constraint evaluation in shape-constrained symbolic regression

C. Haider, F. O. de Franca, G. Kronberger, B. Burlacu - GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 938 - 945, ACM

2022
Genetic programming and FEM simulation for a microscopic residual stress description in polycrystals using neutron diffraction and EBSD data

L. Millán, G. Carro-Sevillano, G. Kronberger, O. Garnica, I. Collado, G. Bokuchava, R. Fernándes, J. I. Hidalgo, P. Halodova, A. Sáez-Maderuelo, G. Gonzáles-Doncel - ICRS 11-The 11th International Conference of Residual Stresses, SF2M, IJL

2022
Extending a physics-based constitutive model using genetic programming

G. Kronberger, E. Kabliman, J. Kronsteiner, M. Kommenda - Applications in Engineering Science, Vol. 9

2022
Comparing Shape-Constrained Regression Algorithms for Data Validation

F. Bachinger - Proceedings of the 18th International Conference on Computer Aided Systems Theory - EUROCAST 2022, Las Palmas de Gran Canaria, Spain (2022)

2022
Shape-constrained Symbolic Regression with NSGA-III.

C. Haider - Proceedings of the 18th International Conference on Computer Aided Systems Theory - EUROCAST 2022, Las Palmas de Gran Canaria, Spain (2022)

2022
Identifying Differential Equations to Predict Blood Glucose using Sparse Identification of Nonlinear Systems.

D. Jödicke, D. Parra, G. Kronberger, S. M. Winkler - Proceedings of the 18th International Conference on Computer Aided Systems Theory - EUROCAST 2022, Las Palmas de Gran Canaria, Spain (2022)

2022
Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization

L. Kammerer, G. Kronberger, M. Kommenda - Proceedings of the 18th International Conference on Computer Aided Systems Theory - EUROCAST 2022, Las Palmas de Gran Canaria, Spain (2022)

2022
Pattern Mining and Genetic Improvement in Compilers and Interpreters

O. Krauss - Doctoral Thesis

2022
Application of Symbolic Regression in Polymer Processing

W. Roland, M. Kommenda, G. R. Berger-Weber - 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

2022
Grammar-Based Vectorial Genetic Programming for Symbolic Regression

P. Fleck, S. M. Winkler, M. Kommenda, M. Affenzeller - Genetic Programming Theory and Practice XVIII, pp. 21-43

2021
Predicting the Non-Linear Conveying Behavior in Single-Screw Extrusion: A Comparison of Various Data-Based Modeling Approaches used with CFD Simulations

W. Roland, C. Marschik, M. Kommenda, A. Haghofer, S. Dorl, S. Winkler - International Polymer Processing, Vol. 36, Edition 5, pp. 529-544

2021
Multi tree operators for genetic programming to identify optimal energy flow controllers

K. Kefer, R. Hanghofer, P. Kefer, M. Stöger, B. Hofer, M. Affenzeller, S. M. Winkler - GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 1579-1586

2021
Cheating like the neighbors: Logarithmic complexity for fitness evaluation in genetic algorithms

E. Pitzer, M. Affenzeller - 2021 IEEE Congress on Evolutionary Computation (CEC), pp. 1431-1438

2021
Contemporary Symbolic Regression Methods and their Relative Performance

W. La Cava, P. Orzechowski, B. Burlacu, F. O. de França, M. Virgolin, Y. Jin, M. Kommenda, J. H. Moore - arXiv preprint arXiv:2107.14351

2021
Using Shape Constraints for Improving Symbolic Regression Models

C. Haider, F. O. de França, B. Burlacu, G. Kronberger - arXiv preprint

2021
Contemporary symbolic regression methods and their relative performance

W. La Cava, P. Orzechowski, B. Burlacu, F. Olivetti de França, M. Virgolin, Y. Jin, M. Kommenda, J. H. Moore - arXiv preprint

2021
Predicting the Non-Linear Conveying Behavior in Single-Screw Extrusion: A Comparison of Various Data-Based Modeling Approaches used with CFD Simulations

W. Roland, C. Marschik, M. Kommenda, A. Haghofer, S. Dorl, S. Winkler - International Polymer Processing. Vol. 36, Issue 5, pp. 529-544 (2021)

2021
Study of Microscopic Residual Stresses in an Extruded Aluminium Alloy Sample after Thermal Treatmen

L. Millán, G. Bokuchava, J. I. Hidalgo, R. Fernández, G. Kronberger, P. Halodova, A. Sáez, I. Papushkin, O. Garnica, J. Lanchares, G. González-Doncel - Journal of Surface Investigation: X-ray, Synchrotron and Neutron Techniques. 15, pp. 763–767 (2021)

2021
Application of symbolic regression for constitutive modeling of plastic deformation

E. Kabliman, A. H. Kolody, J. Kronsteiner, M. Kommenda, G. Kronberger - Applications in Engineering Science, Volume 6, 100052, Elsevier. (June 2021)

2021
Shape-constrained Symbolic Regression – Improving Extrapolation with Prior Knowledge

G. Kronberger, F. O. de Franca, B. Burlacu, C. Haider, M. Kommenda - Evolutionary Computation (2021)

2021
Estimation of Grain-Level Residual Stresses in a Quenched Cylindrical Sample of Aluminum Alloy AA5083 Using Genetic Programming

L. Millán, G. Kronberger, J. I. Hidalgo, R. Fernández, O. Garnica, G. González-Doncel - Applications of Evolutionary Computation (Conference Proceedings EvoApplications 2021), Vol. 12694, pp. 421.436, (2021)

2021
Continuous improvement and adaptation of predictive models in smart manufacturing and model management

F. Bachinger, G. Kronberger, M. Affenzeller - IET Collaborative Intelligent Manufacturing, Vol. 3, Iss. 1, Special Issue: Selected Papers from Collaborative and Intelligent Manufacturing in Industry 4.0 (ISM @SMM 2019), pp. 48-63, (March 2021)

2021
Empirical analysis of variance for genetic programming based symbolic regression

L. Kammerer, G. Kronberger, S. M. Winkler - GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion

2020
Understanding and Preparing Data of Industrial Processes for Machine Learning Applications

P. Fleck, M. Kügel, M. Kommenda - Computer Aided Systems Theory - EUROCAST 2019, pp. 413-420. Springer. (2020)

2020
Preprocessing and Modeling of Radial Fan Data for Health State Prediction

F. Holzinger, M. Kommenda - Computer Aided Systems Theory - EUROCAST 2019, pp. 312-318. Springer. (2020)

2020
White box vs. black box modeling: on the performance of deep learning, random forests, and symbolic regression in solving regression problems

M. Affenzeller, B. Burlacu, V. Dorfer, S. Dorl, G. Halmerbauer, T. Königswieser, M. Kommenda, J. Vetter, S. M. Winkler - Computer Aided Systems Theory - EUROCAST 2019, pp. 288-295. Springer. (2020)

2020
Towards knowledge-guided genetic improvement

O. Krauss, H. Moessenboeck, M. Affenzeller - ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops, pp. 293-294

2020
A Model-Based Learning Approach for Controlling the Energy Flows of a Residential Household Using Genetic Programming to Perform Symbolic Regression

K. Kefer, R. Hanghofer, P. Kefer, M. Stöger, M. Affenzeller, S. M. Winkler, S. Wagner, B. Hofer - Proceedings of the 18th International Conference on Computer Aided Systems Theory - EUROCAST 2019, Las Palmas de Gran Canaria, Spain (2019)

2020
incremental evaluation for genetic crossover

E. Pitzer, M. Affenzeller - Proceedings of the 18th International Conference on Computer Aided Systems Theory - EUROCAST 2019, Las Palmas de Gran Canaria, Spain (2019)

2020
Genetic programming based evolvement of models of models

M. Semenkina, B. Burlacu, M. Affenzeller - Proceedings of the 18th International Conference on Computer Aided Systems Theory - EUROCAST 2019, Las Palmas de Gran Canaria, Spain (2019)

2020
Smart Manufacturing and Continuous Improvement and Adaptation of Predictive Models

G. Kronberger, F. Bachinger, M. Affenzeller - Procedia Manufacturing, Volume 42. (2020). Part of special issue: International Conference on Industry 4.0 and Smart Manufacturing (ISM 2019)

2020
Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication

L. Kammerer, G. Kronberger, B. Burlacu, S. M. Winkler, M. Kommenda, M. Affenzeller - Genetic Programming Theory and Practice XVII., pp. 79-99. Springer. (2020)

2020
Concept for a Technical Infrastructure for Management of Predictive Models in Industrial Applications

F. Bachinger, G. Kronberger - Computer Aided Systems Theory - EUROCAST 2019, pp. 263-270. Springer. (2020)

2020
White Box vs. Black Box Modeling: On the Performance of Deep Learning, Random Forests, and Symbolic Regression in Solving Regression Problems

Michael Affenzeller, Bogdan Burlacu, Viktoria Dorfer, Sebastian Dorl, Gerhard Halmerbauer, Tilman Königswieser, Michael Kommenda, Julia Vetter, Stephan Winkler - Computer Aided Systems Theory - EUROCAST 2019, pp. 288-295. Springer. (2020)

2020
Identification of Dynamical Systems Using Symbolic Regression

G. Kronberger, L. Kammerer, M. Kommenda - Computer Aided Systems Theory - EUROCAST 2019, pp. 370-377. Springer. (2020)

2020
Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression

B. Burlacu, L. Kammerer, M. Affenzeller, G. Kronberger - Computer Aided Systems Theory - EUROCAST 2019, pp. 361-369. Springer. (2020)

2020
Data Aggregation for Reducing Training Data in Symbolic Regression

L. Kammerer, G. Kronberger, M. Kommenda - Computer Aided Systems Theory - EUROCAST 2019, pp. 378-386. Springer. (2020)

2020
Concept Drift Detection with Variable Interaction Networks

J. Zenisek, G. Kronberger, J. Wolfartsberger, N. Wild, M. Affenzeller - Computer Aided Systems Theory - EUROCAST 2019, pp. 296-303. Springer. (2020)

2020
Multilayer analysis of population diversity in grammatical evolution for symbolic regression

G. Kronberger, J. M. Colmenar, S. M. Winkler, J. I. Hidalgo - Soft Computing. Springer. (2020)

2020
Operon C++: an efficient genetic programming framework for symbolic regression

B. Burlacu, G. Kronberger, M. Kommenda - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion (GECCO ’20), pp. 1562–1570, (July 2020)

2020
Parameter identification for symbolic regression using nonlinear least squares

M. Kommenda, B. Burlacu, G. Kronberger, M. Affenzeller - Genetic Programming and Evolvable Machines 21 (3), 471-501

2020
Analysis of the performance of Genetic Programming on the Blood Glucose Level Prediction Challenge 2020

D. Jödicke, G. Kronberger, J. M. Colmenar, S. M. Winkler, J. M. Velasco, S. Contador, J. I. Hidalgo - CEUR Workshop Proceedings, 2675, 141-145

2019
Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion

W. Roland, M. Kommenda, C.Marschik, J. Miethlinger - Polymers, Vol. 11, No.2, Art. Nr. 334

2019
Parsimony measures in multi-objective genetic programming for symbolic regression

B. Burlacu, G. Kronberger, M. Kommenda, M. Affenzeller - GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion

2019
Prediction of stress-strain curves for aluminium alloys using symbolic regression

E. Kabliman, A. H. Kolody, M. Kommenda, G. Kronberger - AIP Conference Proceedings 2113

2019
Online diversity control in symbolic regression via a fast hash-based tree similarity measure

B. Burlacu, M. Affenzeller, G. Kronberger, M. Kommenda - 2019 IEEE congress on evolutionary computation (CEC), 2175-2182

2019
Using ontologies to express prior knowledge for genetic programming

S. Prieschl, D. Girardi, G. Kronberger - Machine Learning and Knowledge Extraction: Third IFIP TC 5, TC 12, WG 8.4

2019
Cluster analysis of a symbolic regression search space

G. Kronberger, L. Kammerer, B. Burlacu, S. M. Winkler, M. Kommenda, M. Affenzeller - Genetic Programming Theory and Practice XVI, 85-102

2018
Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems

G. Kronberger, M. Kommenda, E. Lughofer, S. Saminger-Platz, A. Promberger, F. Nickel, S. M. Winkler, M. Affenzeller - Applied Soft Computing 69, 610-624

2018
Predicting friction system performance with symbolic regression and genetic programming with factor variables

G. Kronberger, M. Kommenda, A. Promberger, F. Nickel - Proceedings of the Genetic and Evolutionary Computation Conference, 1278-1285

2018
Similarity-based analysis of population dynamics in genetic programming performing symbolic regression

S. M. Winkler, M. Affenzeller, B. Burlacu, G. Kronberger, M. Kommenda, P. Fleck - Genetic Programming Theory and Practice XIV, 1-17

2018
Identification of models for glucose blood values in diabetics by grammatical evolution

J. I. Hidalgo, J. M. Colmenar, J. M. Velasco, G. Kronberger, S. M. Winkler, O. Garnica, J. Lanchares - Handbook of Grammatical Evolution, 367-393

2018
Schema analysis in tree-based genetic programming

B. Burlacu, M. Affenzeller, M. Kommenda, G. Kronberger, S. M. Winkler - Genetic programming theory and practice XV, 17-37

2018
Measures for the evaluation and comparison of graphical model structures

G. Kronberger, B. Burlacu, M. Kommenda, S. M. Winkler, M. Affenzeller - Computer Aided Systems Theory - EUROCAST 2017

2018
Optimization networks for integrated machine learning

M. Kommenda, J Karder, A. Beham, B. Burlacu, G. Kronberger, S. Wagner, M. Affenzeller - Computer Aided Systems Theory - EUROCAST 2017

2018
Offspring selection genetic algorithm revisited: improvements in efficiency by early stopping criteria in the evaluation of unsuccessful individuals

M. Affenzeller, B. Burlacu, S. M. Winkler, M. Kommenda, G. Kronberger, S. Wagner - Computer Aided Systems Theory - EUROCAST 2017

2018
Glucose Prognosis by Grammatical Evolution

J. I. Hidalgo, J. M. Colmenar, G. Kronberger, S. M. Winkler - Computer Aided Systems Theory - EUROCAST 2017

2018
Analysis of schema frequencies in genetic programming

B. Burlacu, M. Affenzeller, M. Kommenda, G. Kronberger, S. M. Winkler - Computer Aided Systems Theory - EUROCAST 2017

2018
Local Optimization and Complexity Control for Symbolic Regression

M. Kommenda - Doctoral Thesis

2018
Box-Type Boom Design Using Surrogate Modeling: Introducing an Industrial Optimization Benchmark

P. Fleck, D. Entner, C. Münzer, M. Kommenda, T. Prante, M. Schwarz, M. Hächl, M. Affenzeller - Evolutionary and Deterministic Methods for Design Optimization and Control With Applications to Industrial and Societal Problems, pp. 355-370

2018
Novel robustness measures for engineering design optimisation

P. Fleck, M. Kommenda, T. Prante, M. Affenzeller - International Journal of Simulation and Process Modelling, Vol. 13, No. 4, pp. 387-401

2017
Towards the design and implementation of optimization networks in HeuristicLab

J. Karder, S. Wagner, A. Beham, M. Kommenda, M. Affenzeller - GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 1209-1214

2017
Data based prediction of blood glucose concentrations using evolutionary methods

J. I. Hidalgo, J. M. Colmenar, G. Kronberger, S. M. Winkler, O. Garnica, J. Lanchares - Journal of medical systems 41, 1-20

2017
Dynamic observation of genotypic and phenotypic diversity for different symbolic regression gp variants

M. Affenzeller, S. M. Winkler, B. Burlacu, G. Kronberger, M. Kommenda, S. Wagner - GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion

2017
Tracing of Evolutionary Search Trajectories in Complex Hypothesis Spaces

B. Burlacu - Doctoral Thesis

2016
Robust fuzzy modeling and symbolic regression for establishing accurate and interpretable prediction models in supervising tribological systems

E. Lughofer, G. Kronberger, M. Kommenda, S. Saminger-Platz, A. Promberger, F. Nickel, S. M. Winkler, M. Affenzeller - International Conference on Fuzzy Computation Theory and Applications 3, 51-63

2016
Predicting glycemia in diabetic patients by evolutionary computation and continuous glucose monitoring

J. M. Colmenar, S. M. Winkler, G. Kronberger, E. Maqueda, M. Botella, J. I. Hidalgo - GECCO '16 Companion: Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion

2016
Heterogeneous model ensembles for short-term prediction of stock market trends

S. M. Winkler, B. Castaño, S. Luengo, S. Schaller, G. Kronberger, M. Affenzeller - International Journal of Simulation and Process Modelling 11 (6), 504-513

2016
Evolving simple symbolic regression models by multi-objective genetic programming

M. Kommenda, G. Kronberger, M. Affenzeller, S. M. Winkler, B. Burlacu - Genetic Programming Theory and Practice XIII, 1-19

2015
Building blocks identification based on subtree sample counts for genetic programming

B. Burlacu, M. Kommenda, M. Affenzeller - 2015 Asia-Pacific Conference on Computer Aided System Engineering (APCASE), pp. 152-157

2015
Simplifying Problem Definitions in the HeuristicLab Optimization Environment

A. Scheibenpflug, A. Beham, M. Kommenda, J. Karder, S. Wagner, M. Affenzeller - GECCO Companion '15: Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, pp. 1101-1108

2015
Heat treatment process parameter estimation using heuristic optimization algorithms

M. Kommenda, B. Burlacu, R. Holecek, A. Gebeshuber, M. Affenzeller - EMSS 2015 Proceeding

2015
Optimization strategies for integrated knapsack and traveling salesman problems

A. Beham, J. Fechter, M. Kommenda, S. Wagner, S. M. Winkler, M. Affenzeller - Computer Aided Systems Theory - EUROCAST 2015

2015
Simulation-based optimization with HeuristicLab: practical guidelines and real-world applications

M. Affenzeller, A. Beham, S. Vonolfen, E. Pitzer, S. M. Winkler, S. Hutterer, M. Kommenda, M. Kofler, G. Kronberger, S. Wagner - pplied Simulation and Optimization: In Logistics, Industrial and Aeronautical Practice, Springer International Publishing, pp. 3-38

2015
On the effectiveness of genetic operations in symbolic regression

B. Burlacu, M. Affenzeller, M. Kommenda - Computer Aided Systems Theory - EUROCAST 2015

2015
Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-Valued Optimization Problem

E. Pitzer, G. Kronberger - Computer Aided Systems Theory - EUROCAST 2015

2015
Using Contextual Information in Sequential Search for Grammatical Optimization Problems

G. Kronberger, M. Kommenda, S. M. Winkler, M. Affenzeller - Computer Aided Systems Theory - EUROCAST 2015

2015
Dynamics of predictability and variable influences identified in financial data using sliding window machine learning

S. M. Winkler, G. Kronberger, M. Kommenda, S. Fink, M. Affenzeller - Computer Aided Systems Theory - EUROCAST 2015

2015
Complexity measures for multi-objective symbolic regression

M. Kommenda, A. Beham, M. Affenzeller, G. Kronberger - Computer Aided Systems Theory - EUROCAST 2015

2015
Sliding window symbolic regression for detecting changes of system dynamics

S. M. Winkler, M. Affenzeller, G. Kronberger, M. Kommenda, B. Burlacu, S. Wagner - Genetic Programming Theory and Practice XII, 91-107

2015
Simulation-based optimization with HeuristicLab: practical guidelines and real-world applications

M. Affenzeller, A. Beham, S. Vonolfen, E. Pitzer, S. M. Winkler, S. Hutterer, M. Kommenda, M. Kofler, G. Kronberger, S. Wagner - Applied Simulation and Optimization: In Logistics, Industrial and Aeronautical Practice

2015
Multi-population genetic programming with data migration for symbolic regression

M. Kommenda, M. Affenzeller, G. Kronberger, B. Burlacu, S. M. Winkler - Computational Intelligence and Efficiency in Engineering Systems, 75-87

2015
Search strategies for grammatical optimization problems - alternatives to grammar-guided genetic programming

G. Kronberger, M. Kommenda - Computational Intelligence and Efficiency in Engineering Systems, 89-102

2015
Methods for genealogy and building block analysis in genetic programming

B. Burlacu, M. Affenzeller, S. M. Winkler, M. Kommenda, G. Kronberger - Computational Intelligence and Efficiency in Engineering Systems, 61-74

2015
Concise Supply-Chain Simulation Optimization for Large Scale Logistic Networks

E. Pitzer, G. Kronberger - Computational Intelligence and Efficiency in Engineering Systems, 429-442

2014
Using FE calculations and data-based system identification techniques to model the nonlinear behavior of PMSMs

G. Bramerdorfer, S. M. Winkler, M. Kommenda, G. Weidenholzer, S. Silber, G. Kronberger, M. Affenzeller, W. Amrhein - IEEE Transactions on Industrial Electronics, Vol. 61, Issue 11, pp. 6454-6462

2014
Genetic programming with data migration for symbolic regression

M. Kommenda, M. Affenzeller, B. Burlacu, G. Kronberger, S. M. Winkler - GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation

2014
Scripting and framework integration in heuristic optimization environments

A. Beham, J Karder, G. Kronberger, S. Wagner, M. Kommenda, A. Scheibenpflug - GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation

2014
Using FE calculations and data-based system identification techniques to model the nonlinear behavior of PMSMs

G. Bramerdorfer, S. M. Winkler, M. Kommenda, G. Weidenholzer, S. Silber, G. Kronberger, M. Affenzeller, W. Amrhein - IEEE Transactions on Industrial Electronics 61 (11), 6454-6462

2014
Gaining deeper insights in symbolic regression

M. Affenzeller, S. M. Winkler, G. Kronberger, M. Kommenda, B. Burlacu, S. Wagner - Genetic Programming Theory and Practice XI, 175-190

2014
On the Identification of Virtual Tumor Markers and Tumor Diagnosis Predictors Using Evolutionary Algorithms

S. M. Winkler, M. Affenzeller, G. Kronberger, M. Kommenda, S. Wagner, W. Jacak, H. Stekel - Advanced Methods and Applications in Computational Intelligence, 95-122

2014
Architecture and design of the HeuristicLab optimization environment

S. Wagner, G. Kronberger, A. Beham, M. Kommenda, A. Scheibenpflug, E. Pitzer, S. Vonolfen, M. Kofler, S. M. Winkler, V. Dorfer, M. Affenzeller - Advanced methods and applications in computational intelligence, 197-261

2013
Effects of constant optimization by nonlinear least squares minimization in symbolic regression

M. Kommenda, G. Kronberger, S. M. Winkler, M. Affenzeller, S. Wagner - GECCO '13 Companion: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation

2013
Visualization of genetic lineages and inheritance information in genetic programming

B. Burlacu, M. Affenzeller, M. Kommenda, S. M. Winkler, G. Kronberger - GECCO '13 Companion: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation

2013
Gpdl: A framework-independent problem definition language for grammar-guided genetic programming

G. Kronberger, M. Kommenda, S. Wagner, H. Dobler - GECCO '13 Companion: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation

2013
PRIMOS: An Integrated Database of Reassessed Protein–Protein Interactions Providing Web-Based Access to In Silico Validation of Experimentally Derived Data

R. Rid, W. Strasser, D. Siegl, C. Frech, M. Kommenda, T. Kern, H. Hintner, J. W. Bauer, K. Önder - ASSAY and Drug Development Technologies, Vol. 11, No. 5, pp. 333-346

2013
Structural synthesis of dispatching rules for dynamic dial-a-ride problems

S. Vonolfen, A. Beham, M. Kommenda, M. Affenzeller - Computer Aided Systems Theory - EUROCAST 2013

2013
On the evolutionary behavior of genetic programming with constants optimization

B. Burlacu, M. Affenzeller, M. Kommenda - Computer Aided Systems Theory - EUROCAST 2013

2013
Variable interaction networks in medical data

S. M. Winkler, G. Kronberger, M. Affenzeller, H. Stekel - International Journal of Privacy and Health Information Management (IJPHIM)

2013
Better GP benchmarks: community survey results and proposals

D. R. White, J. McDermott, M. Castelli, L. Manzoni, B. W. Goldman, G. Kronberger, W. Ja?kowski, U.-M. O'Reilly , S. Luke - Genetic Programming and Evolvable Machines 14, 3-29

2013
Nonlinear least squares optimization of constants in symbolic regression

M. Kommenda, M. Affenzeller, G. Kronberger, S. M. Winkler - Computer Aided Systems Theory-EUROCAST 2013

2013
On the use of estimated tumour marker classifications in tumour diagnosis prediction - a case study for breast cancer

S. M. Winkler, M. Affenzeller, G. Kronberger, M. Kommenda, S. Wagner, V. Dorfer, W. Jacak, H. Stekel - International Journal of Simulation and Process Modelling 8 (1), 29-41

2013
Declarative Modeling and Bayesian Inference of Dark Matter Halos

G. Kronberger - Computer Aided Systems Theory-EUROCAST 2013

2013
Evolution of covariance functions for gaussian process regression using genetic programming

G. Kronberger, M. Kommenda - Computer Aided Systems Theory - EUROCAST 2013

2012
On the architecture and implementation of tree-based genetic programming in HeuristicLab

M. Kommenda, G. Kronberger, S. Wagner, S. M. Winkler, M. Affenzeller - GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation

2012
Algorithm and experiment design with HeuristicLab: An open source optimization environment for research and education

S. Wagner, G. Kronberger - GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation

2012
Constants Optimization in Symbolic Regression

M. Kommenda, G. Kronberger, M. Affenzeller, S. M. Winkler, S. Wagner - 1st Australian Conference on the Applications of Systems Engineering ACASE'12

2012
Combining data mining and ontology engineering to enrich ontologies and linked data

M. C. Suárez-Figueroa, M. D'Aquin, G. Kronberger - Informatica

2012
Enhanced confidence interpretations of gp-based ensemble modeling results

M. Affenzeller, S. M. Winkler, S Forstenlechner, G. Kronberger, M. Kommenda, S. Wagner, H. Stekel - Proceedings of the 24th European Modeling & Simulation Symposium, 340-345

2012
Knowledge discovery through symbolic regression with HeuristicLab

G. Kronberger, S. Wagner, M. Kommenda, A. Beham, A. Scheibenpflug, M. Affenzeller - Machine Learning and Knowledge Discovery in Databases: European Conference on Machine Learning and Knowledge Discovery in Databases

2012
Improving the parsimony of regression models for an enhanced genetic programming process

C. Zavoianu, G. Kronberger, M. Kommenda, D. Zaharie, M. Affenzeller - Computer Aided Systems Theory - EUROCAST 2011

2012
Application of symbolic regression on blast furnace and temper mill datasets

M. Kommenda, G. Kronberger, C. Feilmayr, L Schickmair, M. Affenzeller, S. M. Winkler, S. Wagner - Computer Aided Systems Theory - EUROCAST 2011

2012
Parameter meta-optimization of metaheuristic optimization algorithms

C. Neumüller, S. Wagner, G. Kronberger, M. Affenzeller - Computer Aided Systems Theory - EUROCAST 2011

2012
Using genetic programming in nonlinear model identification

S. M. Winkler, M. Affenzeller, S. Wagner, G. Kronberger, M. Kommenda - Identification for automotive systems. Springer, 89-109

2012
Market basket analysis of retail data: supervised learning approach

G. Kronberger, M. Affenzeller - Computer Aided Systems Theory - EUROCAST 2011

2012
Analysis of selected evolutionary algorithms in feature selection and parameter optimization for data based tumor marker modeling

S. M. Winkler, M. Affenzeller, G. Kronberger, M. Kommenda, S. Wagner, W. Jacak, H. Stekel - Computer Aided Systems Theory - EUROCAST 2011

2011
Overfitting detection and adaptive covariant parsimony pressure for symbolic regression

G. Kronberger, M. Kommenda, M. Affenzeller - GECCO '11: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation

2011
Data mining using unguided symbolic regression on a blast furnace dataset

M. Kommenda, G. Kronberger, C. Feilmayr, M. Affenzeller - Applications of Evolutionary Computation: EvoApplications 2011

2011
Macro-economic time series modeling and interaction networks

G. Kronberger, S. Fink, M. Kommenda, M. Affenzeller - Applications of Evolutionary Computation: EvoApplications 2011

2010
HeuristicLab 3.3: A unified approach to metaheuristic optimization

S. Wagner, A. Beham, G. Kronberger, M. Kommenda, E. Pitzer, M Kofler, S. Vonolfen, S. M. Winkler, V. Dorfer, M. Affenzeller - Proceedings of the seventh Spanish conference on Metaheuristics, Evolutionary and Bioinspired Algorithms (MAEB'2010)

2010
Mutation effects in genetic algorithms with offspring selection applied to combinatorial optimization problems

S. Wagner, M. Affenzeller, A. Beham, G. Kronberger, S. M. Winkler - Proceeding of 22nd European modeling and simulation symposium EMSS

2010
Feature selection in the analysis of tumor marker data using evolutionary algorithms

S. M. Winkler, M. Affenzeller, G. Kronberger, M. Kommenda, S. Wagner, W. Jacak, H. Stekel - 22th European Modeling and Simulation Symposium, EMSS 2010

2010
Symbolic Regression for Knowledge Discovery - Bloat, Overfitting, and Variable Interaction Networks

G. Kronberger - Doctoral Thesis

2009
Improved homology-driven computational validation of protein-protein interactions motivated by the evolutionary gene duplication and divergence hypothesis

C. Frech, M. Kommenda, V. Dorfer, T. Kern, H. Hintner, J. W. Bauer, K. Önder - BMC bioinformatics, Vol. 10, Art. No. 21, pp. 1-13

2009
System identification of blast furnace processes with genetic programming

G. Kronberger, C. Feilmayr, M. Kommenda, S. M. Winkler, M. Affenzeller, T. Burgler - 2009 2nd International Symposium on Logistics and Industrial Informatics, 1-6

2009
Application of genetic programming on temper mill datasets

M. Kommenda, G. Kronberger, S. M. Winkler, M. Affenzeller, S. Wagner, M. Affenzeller, T. Burgler - 2009 2nd International Symposium on Logistics and Industrial Informatics, 1-5

2009
On crossover success rate in genetic programming with offspring selection

G. Kronberger, S. M. Winkler, M. Affenzeller, S. Wagner - European Conference on Genetic Programming, 232-243

2009
Metaheuristic optimization

M. Affenzeller, A. Beham, M. Kofler, G. Kronberger, SA Wagner, S. M. Winkler - Hagenberg Research, 103-155

2009
On the success rate of crossover operators for genetic programming with offspring selection

G. Kronberger, S. M. Winkler, M. Affenzeller, A. Beham, S. Wagner - Computer Aided Systems Theory-EUROCAST 2009

2009
Priority rule generation with a genetic algorithm to minimize sequence dependent setup costs

M. Kofler, S. Wagner, A. Beham, G. Kronberger, M. Affenzeller - Computer Aided Systems Theory-EUROCAST 2009

2009
Model driven rapid prototyping of heuristic optimization algorithms

S. Wagner, G. Kronberger, A. Beham, S. M. Winkler, M. Affenzeller - Computer Aided Systems Theory-EUROCAST 2009

2008
Simulation optimization with HeuristicLab

A. Beham, M. Affenzeller, S. Wagner, G. Kronberger - Proceedings of the 20th European Modeling and Simulation Symposium, 75-80

2008
Data mining via distributed genetic programming agents

G. Kronberger, S. M. Winkler, M. Affenzeller, S. Wagner - Proceedings of the 20th European Modeling and Simulation Symposium, 95-99

2008
Modeling of heuristic optimization algorithms

S. Wagner, G. Kronberger, A. Beham, S. M. Winkler, M. Affenzeller - Proceedings of the 20th European Modeling and Simulation Symposium, 106-111

2008
Evolutionary System Identification - Modern Concepts and Practical Applications

S. Winkler - Doctoral Thesis

2007
Benefits of plugin-based heuristic optimization software systems

S. Wagner, S. M. Winkler, E. Pitzer, G. Kronberger, A. Beham, R. Braune, M. Affenzeller - Computer Aided Systems Theory - EUROCAST 2007