Publications

2014

  • A. Beham, G. K. Kronberger, J. Karder, M. Kommenda, A. Scheibenpflug, S. Wagner, M. Affenzeller - Integrated Simulation and Optimization in HeuristicLab - Proceedings of the 26th European Modeling and Simulation Symposium EMSS 2014, Bordeaux, Frankreich, 2014, pp. 418-42

2015

  • M. Affenzeller, A. Beham, S. Vonolfen, E. Pitzer, S. M. Winkler, S. Hutterer, M. Kommenda, M. Kofler, G. K. Kronberger, S. Wagner - Simulation-Based Optimization with HeuristicLab in Applied Simulation and Optimization (Contributions to Book: Part/Chapter/Section 1), (Editors: M. Mujica Mota, I. De La Mota, D. Guimarans Serrano) - Springer, 2015, pp. 1-38
  • S. M. Winkler, M. Affenzeller, G. Kronberger, M. Kommenda, B. Burlacu, and S. Wagner: Sliding Window Symbolic Regression for Detecting Changes of System Dynamics. In Genetic Programming Theory and Practice XII, Springer, 2015.

  • A. Beham, M. Kommenda, S. Wagner, S. M. Winkler, M. Affenzeller: Optimization Strategies for Integrated Knapsack and Traveling Salesman Problems, in R. Moreno-Diaz, F.Pichler, A. Quesada-Arencibia (Eds.): Lecture Notes in Computer Science (LNCS 9520), Springer, 2015, pp. 359-366.

  • A. Beham, M. Affenzeller, E. Pitzer: Metaheuristic Algorithms for the Quadratic Assignment Problem: Performance and Comparison, in R. Klempous, J. Nikodem: Innovative Technologies in Management and Science, Innovative Technologies in Management and Science, Nummer 7, Springer, 2015, pp. 91-110.

  • B. Burlacu, M. Affenzeller, M. Kommenda: On the Effectiveness of Genetic Operations in Symbolic Regression, in R. Moreno-Diaz, F.Pichler, A. Quesada-Arencibia (Eds.): Lecture Notes in Computer Science (LNCS 9520), Springer, 2015, pp. 367-374.

  • B. Burlacu, M. Kommenda, M. Affenzeller: Building Blocks Identification Based on Subtree Sample Counts for Genetic Programming, in Proceedings of the 3rd Asia-Pacific Conference on Computer Aided System Engineering Conference 2015, 2015.

  • B. Burlacu, M. Affenzeller, S. M. Winkler, M. Kommenda, G. K. Kronberger - Methods for Genealogy and Building Blocks Analysis in Genetic Programming in Computational Intelligence and Efficiency in Engineering Systems (Contributions to Book: Part/Chapter/Section 5), (Editors: G. Borowik, Z. Chaczko, L.G. Ford, W. Jacak, T. Luba) - Springer, 2015, pp. 61-74.

  • J. Fechter, A. Beham, S. Wagner, M. Affenzeller: Modeling a Lot-Aware Slab Stack Shuffling Problem, in R. Moreno-Diaz, F.Pichler, A. Quesada-Arencibia (Eds.): Lecture Notes in Computer Science (LNCS 9520), Springer, 2015, pp. 334-341.

  • J. Fechter, A. Beham, S. Wagner: Modelling a Clustered Generalized Quadratic Assignment Problem, in Proceedings of the 27th European Modeling and Simulation Symposium EMSS 2015, 2015.

  • M. Kommenda, A. Beham, M. Affenzeller, G. Kronberger: Complexity Measures for Multi-Objective Symbolic Regression, in R. Moreno-Diaz, F.Pichler, A. Quesada-Arencibia (Eds.): Lecture Notes in Computer Science (LNCS 9520), Springer, 2015, pp. 409-416.

  • M. Kommenda, M. Affenzeller, G. Kronberger, B. Burlacu, S. M. Winkler: Multi-Population Genetic Programming with Data Migration for Symbolic Regression in Computational Intelligence and Efficiency in Engineering Systems , in G. Borowik, Z. Chaczko, L.G. Ford, W. Jacak, T. Luba: Computational Intelligence and Efficiency in Engineering Systems, Nummer 6, Springer, 2015, pp. 75-87.

  • M. Kommenda, M. Affenzeller, G. K. Kronberger, B. Burlacu, S. M. Winkler - Multi-Population Genetic Programming with Data Migration for Symbolic Regression in Computational Intelligence and Efficiency in Engineering Systems (Contributions to Book: Part/Chapter/Section 6), (Editors: G. Borowik, Z. Chaczko, L.G. Ford, W. Jacak, T. Luba) - Springer, 2015, pp. 75-87.

  • G. K. Kronberger, M. Kommenda - Search Strategies for Grammatical Optimization Problems – Alternatives to Grammar-Guided Genetic Programming in Computational Intelligence and Efficiency in Engineering Systems (Contributions to Book: Part/Chapter/Section 7), (Editors: G. Borowik, Z. Chaczko, L.G. Ford, W. Jacak, T. Luba) - Springer, 2015, pp. 89-102.

  • A. Petrakova, M. Affenzeller, G. Merkurjeva : Heterogeneous versus Homogeneous Machine Learning Ensemble. In Information Technology and Management Science 01/2015; 18(1). DOI: 10.1515/itms-2015-0021

  • A. Scheibenpflug, A. Beham, M. Kommenda, J. Karder, S. Wagner, M. Affenzeller: Simplifying Problem Definitions in the HeuristicLab Optimization Environment, in Companion Publication of the 2015 Genetic and Evolutionary Computation Conference, GECCO'15, 2015, pp. 1101-1108.

  • S. Wagner, M. Affenzeller, A. Scheibenpflug: Automatic Adaption of Operator Probabilities in Genetic Algorithms with Offspring Selection, in R. Moreno-Diaz, F.Pichler, A. Quesada-Arencibia (Eds.): Lecture Notes in Computer Science (LNCS 9520), Springer, 2015, pp. 433-438.

  • S. M. Winkler, B. Castaño, S. Luengo, S. Schaller, G. Kronberger, M. Affenzeller: HETEROGENEOUS MODEL ENSEMBLES FOR SHORT-TERM PREDICTION OF STOCK MARKET TRENDS. In: Int. J. Simulation and Process Modelling, 2015.

2016

  • M. Kommenda, G.l Kronberger, M. Affenzeller, S. M. Winkler, B. Burlacu: Evolving Simple Symbolic Regression Models by Multi-objective Genetic Programming. In Genetic Programming Theory and Practice XIII. Accepted for publication 2016.