• 2019

    Article in Journal

    Carnein, M., & Trautmann, H. (2019). Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms. Business and Information Systems Engineering (BISE), 61(3), 277–297.
    More details BibTeX

    Kerschke, P., Hoos, H. H., Neumann, F., & Trautmann, H. (2019). Automated Algorithm Selection: Survey and Perspectives. Evolutionary Computation (ECJ), 27(1), 3–45.
    More details BibTeX Full text DOI

    Kerschke, P., & Trautmann, H. (2019). Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning. Evolutionary Computation (ECJ), 27(1), 99–127.
    More details BibTeX Full text DOI

    Conference Paper

    Bossek, J., & Trautmann, H. (2019). Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. In Battiti, R., Brunato, M., Kotsireas, I., & Pardalos, P. (Eds.), Learning and Intelligent Optimization (pp. 215–219). Lecture Notes in Computer Science: Vol. 11353. Cham: Springer.
    More details BibTeX

    Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2019). Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary Algorithm. In Deb, K., Goodman, E., Coello, C. C. A., Klamroth, K., Miettinen, K., Mostaghim, S., & Reed, P. (Eds.), Evolutionary Multi-Criterion Optimization (EMO) (pp. 516–528). Lecture Notes in Computer Science: Vol. 11411. Springer International Publishing.
    More details BibTeX DOI

    Bossek, J., Kerschke, P., Neumann, A., Wagner, M., Neumann, F., & Trautmann, H. (2019). Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators. In Proceedings of the 15th ACM/SIGEVO Workshop on Foundations of Genetic Algorithms (FOGA XV), Potsdam, Germany, 58–71.
    More details BibTeX DOI

    Carnein, M., Homann, L., Trautmann, H., & Vossen, G. (2019). A Recommender System Based on Omni-Channel Customer Data. In Proceedings of the 21st IEEE Conference on Business Informatics (CBI' 19), Moscow, Russia.
    More details BibTeX

    Carnein, M., & Trautmann, H. (2019). Customer Segmentation Based on Transactional Data Using Stream Clustering. In Proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD '19), Macau, China.
    More details BibTeX

    Carnein, M., Trautmann, H., Bifet, A., & Pfahringer, B. (2019). Towards Automated Configuration of Stream Clustering Algorithms. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD '19), Würzburg, Germany. (Accepted)
    More details BibTeX

    Grimme, C., Kerschke, P., Emmerich, M. T. M., Preuss, M., Deutz, A. H., & Trautmann, H. (2019). Sliding to the Global Optimum: How to Benefit from Non-Global Optima in Multimodal Multi-Objective Optimization. In Proceedings of the International Global Optimization Workshop (LeGO 2018), Leiden, The Netherlands, 020052-1-020052-4.
    More details BibTeX Full text DOI

    Grimme, C., Kerschke, P., & Trautmann, H. (2019). Multimodality in Multi-Objective Optimization — More Boon than Bane?. In Proceedings of the 10th International Conference on Evolutionary Multi-Criterion Optimization (EMO), East Lansing, MI, USA, 126–138.
    More details BibTeX Full text DOI

  • 2018

    Article in Journal

    Carnein, M., & Trautmann, H. (2018). evoStream — Evolutionary Stream Clustering Utilizing Idle Times. Big Data Research, 14, 101–111.
    More details BibTeX DOI

    Kerschke, P., Kotthoff, L., Bossek, J., Hoos, H. H., & Trautmann, H. (2018). Leveraging TSP Solver Complementarity through Machine Learning. Evolutionary Computation (ECJ), 26(4), 597–620.
    More details BibTeX Full text DOI

    Kerschke, P., Wang, H., Preuss, M., Grimme, C., Deutz, A., Trautmann, H., & Emmerich, M. (2018). Search Dynamics on Multimodal Multi-Objective Problems. Evolutionary Computation (ECJ), 0, 1–30. (In press)
    More details BibTeX Full text DOI

    Li, L., Wang, Y., Trautmann, H., Jing, N., & Emmerich, M. (2018). Multiobjective evolutionary algorithms based on target region preferences. Swarm and Evolutionary Computation, 40, 196–215.
    More details BibTeX Full text DOI

    Conference Paper

    Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2018). Local Search Effects in Bi-Objective Orienteering. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '18), Kyoto, Japan, 585–592.
    More details BibTeX DOI

    Kerschke, P., Bossek, J., & Trautmann, H. (2018). Parameterization of State-of-the-Art Performance Indicators: A Robustness Study Based on Inexact TSP Solvers. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '18) Companion, Kyoto, Japan, 1737–1744.
    More details BibTeX Full text DOI

    van Engelen, J., van Lier, J., Takes, F., & Trautmann, H. (2018). Accurate WiFi based indoor positioning with continuous location sampling. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD), Dublin, Ireland, 524–540.
    More details BibTeX

  • 2017

    Article in Journal

    Grimme, C., Preuss, M., Adam, L., & Trautmann, H. (2017). Social Bots: Human-Like by Means of Human Control?. Big Data, 5(4), 279–293.
    More details BibTeX Full text DOI

    Conference Paper

    Carnein, M., Assenmacher, D., & Trautmann, H. (2017). An Empirical Comparison of Stream Clustering Algorithms. In Proceedings of the ACM International Conference on Computing Frontiers (CF '17), Siena, Italy, 361–365.
    More details BibTeX DOI

    Carnein, M., Assenmacher, D., & Trautmann, H. (2017). Stream Clustering of Chat Messages with Applications to Twitch Streams. In de Cesare, S., & Ulrich, F. (Eds.), Proceedings of the 36th International Conference on Conceptual Modeling (ER'17) (pp. 79–88). Springer International Publishing.
    More details BibTeX DOI

    Carnein, M., Heuchert, M., Homann, L., Trautmann, H., Vossen, G., Becker, J., & Kraume, K. (2017). Towards Efficient and Informative Omni-Channel Customer Relationship Management. In de Cesare, S., & Ulrich, F. (Eds.), Proceedings of the 36th International Conference on Conceptual Modeling (ER'17) (pp. 69–78). Lecture Notes in Computer Science: Vol. 10651. Springer International Publishing.
    More details BibTeX DOI

    Carnein, M., Homann, L., Trautmann, H., Vossen, G., & Kraume, K. (2017). Customer Service in Social Media — An Empirical Study of the Airline Industry. In Bernhard, M. a. N. R. a. H. S. a. M. K. a. A. T. a. O. K. a. M. W. (Ed.), Proceedings of the 17th Conference on Database Systems for Business, Technology, and Web (BTW '17) (pp. 33–40). Lecture Notes in Informatics (LNI): Vol. P-266. Gesellschaft für Informatik.
    More details BibTeX

    Chapter in Book

    Adrián, S. H. V., Lara, A., Trautmann, H., Rudolph, G., & Schütze, O. (2017). The Directed Search Method for Unconstrained Parameter Dependent Multi-objective Optimization Problems. In Schütze, O., Trujillo, L., Legrand, P., & Maldonado, Y. (Eds.), NEO 15 (pp. 281–330). Cham: Springer International Publishing.
    More details BibTeX Full text DOI

    Li, L., Yevseyeva, I., Basto-Fernandes, V., Trautmann, H., Jing, N., & Emmerich, M. (2017). Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms. In Trautmann, H., Rudolph, G., Klamroth, K., Schütze, O., Wiecek, M., Jin, Y., & Grimme, C. (Eds.), Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings (pp. 406–421). Cham: Springer International Publishing.
    More details BibTeX Full text DOI

    Tierney, K., Handali, J., Grimme, C., & Trautmann, H. (2017). Multi-objective Optimization for Liner Shipping Fleet Repositioning. In Trautmann, H., Rudolph, G., Klamroth, K., Schütze, O., Wiecek, M., Jin, Y., & Grimme, C. (Eds.), Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings (pp. 622–638). Cham: Springer International Publishing.
    More details BibTeX Full text DOI

    Report

    Trautmann, H., Vossen, G., Homann, L., Carnein, M., & Kraume, K. (2017). Challenges of Data Management and Analytics in Omni-Channel CRM. In Becker, J., Backhaus, K., Dugas, M., Hellingrath, B., Hoeren, T., Klein, S., Kuchen, H., Trautmann, H., & Vossen, G. (Eds.), ERCIS Working Papers: Vol. 28. Münster: European Research Center for Information Systems.
    More details BibTeX

  • 2016

    Article in Journal

    Neumann, F., & Trautmann, H. (2016). Working Group Report: Bridging the Gap Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211). Dagstuhl Reports, 5(5), 78–79.
    More details BibTeX Full text DOI

    Rudolph, G., Schütze, O., Grimme, C., Domínguez-Medina, C., & Trautmann, H. (2016). Optimal averaged Hausdorff archives for bi-objective problems: theoretical and numerical results. Computational Optimization and Applications, 64(2), 589–618.
    More details BibTeX Full text DOI

    Schütze, O., Sosa, H. V., Trautmann, H., & Rudolph, G. (2016). The Hypervolume based Directed Search Method for Multi-Objective Optimization Problems. Journal of Heuristics, 22(3), 273–300.
    More details BibTeX DOI

    Conference Paper

    Blot, A., Hoos, H., Jourdan, L., Marmion, M., & Trautmann, H. (2016). MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework. In Proceedings of the Learning and Intelligent Optimization, 10th International Conference, Ischia. (Accepted)
    More details BibTeX

    Bossek, J., & Trautmann, H. (2016). Evolving Instances for Maximizing Performance Differences of State-of-The-Art Inexact TSP Solvers. In Festa, P., Sellmann, M., & Vanschoren, J. (Eds.), Learning and Intelligent Optimization (pp. 48–59). Lecture Notes in Computer Science: Vol. 10079. Springer International Publishing.
    More details BibTeX DOI

    Bossek, J., & Trautmann, H. (2016). Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. In Adorni, G., Cagnoni, S., Gori, M., & Maratea, M. (Eds.), AI*IA 2016 Advances in Artificial Intelligence (pp. 3–12). Lecture Notes in Computer Science: Vol. 10037. Cham: Springer.
    More details BibTeX DOI

    Kerschke, P., Preuss, M., Wessing, S., & Trautmann, H. (2016). Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '16), Denver, CO, USA, 229–236.
    More details BibTeX Full text DOI

    Kerschke, P., & Trautmann, H. (2016). The R-Package FLACCO for Exploratory Landscape Analysis with Applications to Multi-Objective Optimization Problems. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Vancouver, BC, Kanada.
    More details BibTeX Full text DOI

    Kerschke, P., Wang, H., Preuss, M., Grimme, C., Deutz, A., Trautmann, H., & Emmerich, M. (2016). Towards Analyzing Multimodality of Multiobjective Landscapes. In Proceedings of the 14th International Conference on Parallel Problem Solving from Nature (PPSN XIV), Edinburgh, Scotland, 962–972.
    More details BibTeX Full text DOI

    Chapter in Book

    Rudolph, G., Schütze, O., & Trautmann, H. (2016). On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front. In Squillero, G., & Burelli, P. (Eds.), Applications of Evolutionary Computation: 19th European Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II (pp. 42–55). Cham: Springer International Publishing.
    More details BibTeX Full text DOI

  • 2015

    Article in Journal

    Brockhoff, D., Wagner, T., & Trautmann, H. (2015). R2 Indicator Based Multiobjective Search. Evolutionary Computation Journal, 23(3), 369–395.
    More details BibTeX Full text DOI

    Mersmann, O., Preuss, M., Trautmann, H., Bischl, B., & Weihs, C. (2015). Analyzing the BBOB Results by Means of Benchmarking Concepts. Evolutionary Computation Journal, 23(1), 161–185.
    More details BibTeX

    Conference Paper

    Chinnov, A., Kerschke, P., Meske, C., Stieglitz, S., & Trautmann, H. (2015). An Overview of Topic Discovery in Twitter Communication through Social Media Analytics. In Proceedings of the 20th Americas Conference on Information Systems (AMCIS '15), Puerto Rico, 1–10.
    More details BibTeX Full text

    Grimme, C., Meisel, S., Trautmann, H., Rudolph, G., & Wölck, M. (2015). Multi-Objective Analysis of Approaches to Dynamic Routing Of a Vehicle. In Proceedings of the European Conference On Information Systems, Münster, Germany.
    More details BibTeX

    Kerschke, P., Preuss, M., Wessing, S., & Trautmann, H. (2015). Detecting Funnel Structures by Means of Exploratory Landscape Analysis. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '15), Madrid, Spain, 265–272.
    More details BibTeX Full text DOI

    Kotthoff, L., Kerschke, P., Hoos, H. H., & Trautmann, H. (2015). Improving the State of the Art in Inexact TSP Solving using Per-Instance Algorithm Selection. In Dhaenens, C., Jourdan, L., & Marmion, M.-E. (Eds.), Learning and Intelligent Optimization, 9th International Conference (pp. 202–217). Cham: Springer International Publishing.
    More details BibTeX Full text DOI

    Meisel, S., Grimme, C., Bossek, J., Wölck, M., Rudolph, G., & Trautmann, H. (2015). Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle. In Proceedings of the Genetic and Evolutionary Computation Conference, Madrid, Spain, 425–432.
    More details BibTeX DOI

    Sosa, H. V., Schütze, O., Trautmann, H., & Rudolph, G. (2015). On the Behavior of Stochastic Local Search within Parameter Dependent MOPs. In Proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization, Guimaraes, Portugal, 126–140.
    More details BibTeX DOI

    Abstract / Poster

    Martí, L., Grimme, C., Kerschke, P., Trautmann, H., & Rudolph, G. (2015). Averaged Hausdorff Approximations of Pareto Fronts Based on Multiobjective Estimation of Distribution Algorithms. Poster session presented at the Genetic and Evolutionary Computation Conference (GECCO '15), Madrid, Spain.
    More details BibTeX Full text DOI

    Other

    Martí, L., Grimme, C., Kerschke, P., Trautmann, H., & Rudolph, G. (2015). Averaged Hausdorff Approximations of Pareto Fronts based on Multiobjective Estimation of Distribution Algorithms.
    More details BibTeX Full text

  • 2014

    Conference Paper

    Rudolph, G., Grimme, C., Schütze, O., & Trautmann, H. (2014). An Aspiration Set EMOA Based on Averaged Hausdorff Distances. In Proceedings of the Learning and Intelligent OptimizatioN Conference (LION 8), Gainesville, Florida, USA, 153–156.
    More details BibTeX Full text

    Wessing, S., Preuss, M., & Trautmann, H. (2014). Stopping Criteria for Multimodal Optimization. In Proceedings of the Parallel Problem Solving from Nature — PPSN XIII, Ljubljana, Slovenia, 141–150.
    More details BibTeX Full text DOI

    Chapter in Book

    Kerschke, P., Preuss, M., Hernández, C., Schütze, O., Sun, J.-Q., Grimme, C., Rudolph, G., Bischl, B., & Trautmann, H. (2014). Cell Mapping Techniques for Exploratory Landscape Analysis. In Tantar, A.-A., Tantar, E., Sun, J.-Q., Zhang, W., Ding, Q., Schütze, O., Emmerich, M. T. M., Legrand, P., Del, M. P., & Coello, C. C. A. (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (pp. 115–131). Advances in Intelligent Systems and Computing: Vol. 288. Cham: Springer International Publishing.
    More details BibTeX Full text DOI

    Rudolph, G., Schütze, O., Grimme, C., & Trautmann, H. (2014). A Multiobjective Evolutionary Algorithm Guided by Averaged Hausdorff Distance to Aspiration Sets. In Tantar, A., Tantar, E., Sun, J., Zhang, W., Ding, Q., Schütze, O., Emmerich, M., Legrand, P., Del, M. P., & Coello, C. C. (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (pp. 261–273). Advances in Intelligent Systems and Computing: Vol. 288. Springer International Publishing.
    More details BibTeX Full text DOI

  • 2013

    Article in Journal

    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 Salesman Problem. Annals of Mathematics and Artificial Intelligence, 69, 151–182.
    More details BibTeX

    Trautmann, H., Wagner, T., Biermann, D., & Weihs, C. (2013). Indicator-based Selection in Evolutionary Multiobjective Optimization Algorithms Based On the Desirability Index. Journal of Multi-Criteria Decision Analysis, 20(5-6), 319–337.
    More details BibTeX

    Conference Paper

    Dominguez-Medina, C., Rudolph, G., Schütze, O., & Trautmann, H. (2013). Evenly spaced Pareto fronts of quad-objective problems using PSA partitioning technique. In Proceedings of the 2013 IEEE Congress on Evolutionary Computation (CEC), Cancun, Mexico, 3190–3197.
    More details BibTeX

    Nallaperuma, S., Wagner, M., Neumann, F., Bischl, B., Mersmann, O., & Trautmann, H. (2013). A Feature-Based Comparison of Local Search and the Christofides Algorithm for the Travelling Salesperson Problem. In Proceedings of the FOGA, Adelaide, Australia, 147–160.
    More details BibTeX

    Preuss, M., Kozakowski, D., Hagelbäck, J., & Trautmann, H. (2013). Reactive strategy choice in StarCraft by means of Fuzzy Control. In Proceedings of the 2013 IEEE Conference on Computational Inteligence in Games (CIG), Niagara Falls, ON, Canada, 1–8.
    More details BibTeX

    Rudolph, G., Trautmann, H., Sengupta, S., & Schütze, O. (2013). Evenly Spaced Pareto Front Approximations for Tricriteria Problems Based on Triangulation. In Purshouse, R., Fleming, P., Fonseca, C., Greco, S., & Shaw, J. (Eds.), Evolutionary Multi-Criterion Optimization — 7th International Conference, EMO 2013, Sheffield, UK, Proceedings (pp. 443–458). Lecture Notes in Computer Science: Vol. 7811. Springer.
    More details BibTeX

    Sosa-Hernandez, V., Schütze, O., Rudoph, G., & Trautmann, H. (2013). Directed Search Method for Indicator-based Multi-objective Evolutionary Algorithms. In Proceedings of the GECCO 2013, Amsterdam (Netherlands), 1699–1702.
    More details BibTeX DOI

    Trautmann, H., Wagne, T., & Brockhoff, D. (2013). R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection. In Proceedings of the Learning and Intelligent Optimization Conference 7, Catania, Italy, 70–74.
    More details BibTeX

    Wagner, T., Trautmann, H., & Brockhoff, D. (2013). Preference Articulation by Means of the R2 Indicator. In Purshouse, R. C., Fleming, P. J., Fonseca, C. M., Greco, S., & Shaw, J. (Eds.), Evolutionary Multi-Criterion Optimization — 7th International Conference, EMO 2013, Sheffield, UK, Proceedings (pp. 81–95). Lecture Notes in Computer Science: Vol. 7811. Springer.
    More details BibTeX

    Chapter in Book

    Sosa, H. V., Schütze, O., Rudolph, G., & Trautmann, H. (2013). The Directed Search Method for Pareto Front Approximations with Maximum Dominated Hypervolume. In Emmerich, M., Deutz, A., Schuetze, O., Bäck, T., Tantar, A., Moral, P., Legrand, P., Bouvry, P., & Coello, C. (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV (pp. 189–205). Advances in Intelligent Systems and Computing: Vol. 227. Springer International Publishing.
    More details BibTeX Full text DOI

    Trautmann, H., Rudolph, G., Dominguez-Medina, C., & Schütze, O. (2013). Finding Evenly Spaced Pareto Fronts for Three-Objective Optimization Problems. In Schütze, O., Coello, C. C., Tantar, A., Tantar, E., Bouvry, P., Del, M. P., & Legrand, P. (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II (pp. 89–105). Advances in Intelligent Systems and Computing: Vol. 175. Springer Berlin Heidelberg.
    More details BibTeX Full text DOI

  • 2012

    Article in Journal

    Bischl, B., Mersmann, O., Trautmann, H., & Weihs, C. (2012). Resampling Methods in Model Validation. Evolutionary Computation Journal, 20(2), 249–275.
    More details BibTeX DOI

    Rudolph, G., Trautmann, H., & Schütze, O. (2012). Homogene Approximation der Paretofront bei mehrkriteriellen Kontrollproblemen. at-Automatisierungstechnik, 60, 610–621.
    More details BibTeX DOI

    Conference Paper

    Bischl, B., Mersmann, O., Trautmann, H., & Preuss, M. (2012). Algorithm selection based on exploratory landscape analysis and cost-sensitive learning. In Soule, T., & Moore, J. (Eds.), Genetic and Evolutionary Computation Conference, GECCO '12, Philadelphia, PA, USA (pp. 313–320). ACM.
    More details BibTeX

    Brockhoff, D., Wagner, T., & Trautmann, H. (2012). On the Properties of the R2 Indicator. In Soule, T., & others, (Eds.), Proc. 14th Int'l. Genetic and Evolutionary Computation Conference (GECCO '12) (pp. 465–472). ACM.
    More details BibTeX DOI

    Mersmann, O., Bischl, B., Bossek, J., Trautmann, H., Wagner, M., & Neumann, F. (2012). Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness. In Hamadi, Y., & Schoenauer, M. (Eds.), Learning and Intelligent Optimization — 6th International Conference, LION 6, Paris (pp. 115–129). Lecture Notes in Computer Science: Vol. 7219. Springer.
    More details BibTeX

  • 2011

    Article in Journal

    Naujoks, B., Trautmann, H., Wessing, S., & Weihs, C. (2011). Advanced concepts for multi-objective evolutionary optimization in aircraft industry. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 225, 1081–1096.
    More details BibTeX DOI

    Conference Paper

    Gerstl, K., Rudolph, G., Schütze, O., & Trautmann, H. (2011). Finding evenly spaced fronts for multiobjective control via averaging Hausdorff-measure. In Proceedings of 8th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), 1–6.
    More details BibTeX DOI

    Mersmann, O., Bischl, B., Trautmann, H., Preuss, M., Weihs, C., & Rudolph, G. (2011). Exploratory landscape analysis. In Proceedings of the 13th annual conference on Genetic and evolutionary computation, 829–836.
    More details BibTeX

    Wagner, T., Trautmann, H., & Marti, L. (2011). A Taxonomy of Online Stopping Criteria for Multi-Objective Evolutionary Algorithms. In Takahashi, R., Deb, K., Wanner, E., & Greco, S. (Eds.), Evolutionary Multi-Criterion Optimization (pp. 16–30). Lecture Notes in Computer Science: Vol. 6576. Springer Berlin — Heidelberg.
    More details BibTeX

  • 2010

    Article in Journal

    Azene, Y., Roy, R., Farrugia, D., Onisa, C., Mehnen, J., & Trautmann, H. (2010). Work roll cooling system design optimisation in presence of uncertainty and constrains. CIRP Journal of Manufacturing Science and Technology, 2, 290–298.
    More details BibTeX DOI

    Wagner, T., & Trautmann, H. (2010). Integration of Preferences in Hypervolume-Based Multiobjective Evolutionary Algorithms by Means of Desirability Functions. IEEE Transactions on Evolutionary Computation, 14(5), 688–701.
    More details BibTeX DOI

    Conference Paper

    Bischl, B., Mersmann, O., & Trautmann, H. (2010). Resampling Methods in Model Validation. In Bartz-Beielstein, T., Chiarandini, M., Paquete, L., & Preuss, M. (Eds.), Proceedings of the Workshop on Experimental Methods for the Assessment of Computational Systems (WEMACS 2010), Algorithm Engineering Report TR10-2-007. Department of Computer Science, TU Dortmund University.
    More details BibTeX

    Ding, J., Wessing, S., Trautmann, H., Mehnen, J., & Naujoks, B. (2010). Sequential Parameter Optimisation for Multi-Objective Evolutionary Optimisation of Additive Layer Manufacturing. In Teti, R. (Ed.), Proceedings of the 7th CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME '10). Capri, Italy: Copyright C.O.C. Com. org. Conv.
    More details BibTeX

    Mersmann, O., Preuss, M., & Trautmann, H. (2010). Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis. In Schaefer, R., Cotta, C., Kolodziej, J., & Rudolph, G. (Eds.), 11th International Conference on Parallel Problem Solving from Nature — PPSN XI, Proceedings, Part I (pp. 73–82). Lecture Notes in Computer Science: Vol. 6238. Springer.
    More details BibTeX

    Mersmann, O., Trautmann, H., Naujoks, B., & Weihs, C. (2010). On the Distribution of EMOA Hypervolumes. In Blum, C., & Battiti, R. (Eds.), Learning and Intelligent Optimization, 4th International Conference, LION 4, Venice, Italy (pp. 333–337). Lecture Notes in Computer Science: Vol. 6073. Springer.
    More details BibTeX

    Mersmann, O., Trautmann, H., Naujoks, B., & Weihs, C. (2010). Benchmarking evolutionary multiobjective optimization algorithms. In Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2010, Barcelona, Spain, 1–8.
    More details BibTeX

    Mostaghim, S., Trautmann, H., & Mersmann, O. (2010). Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities. In Schaefer, R., Cotta, C., Kolodziej, J., & Rudolph, G. (Eds.), 11th International Conference on Parallel Problem Solving from Nature — PPSN XI, Proceedings, Part II (pp. 101–110). Lecture Notes in Computer Science: Vol. 6239. Springer.
    More details BibTeX

    Voss, T., Trautmann, H., & Igel, C. (2010). New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization. In Schaefer, R., Cotta, C., Kolodziej, J., & Rudolph, G. (Eds.), 11th International Conference on Parallel Problem Solving from Nature — PPSN XI, Proceedings, Part II (pp. 260–269). Lecture Notes in Computer Science: Vol. 6239. Springer.
    More details BibTeX

    Wagner, T., & Trautmann, H. (2010). Online convergence detection for evolutionary multi-objective algorithms revisited. In Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2010, Barcelona, Spain, 1–8.
    More details BibTeX

  • 2009

    Article in Journal

    Trautmann, H., & Mehnen, J. (2009). Statistical Methods for Improving Multi-objective Evolutionary Optimisation. International Journal of Computational Intelligence Research, 5(2), 72–78.
    More details BibTeX DOI

    Trautmann, H., & Mehnen, J. (2009). Preference-Based Pareto-Optimization in Certain and Noisy Environments. Engineering Optimization, 41, 23–38.
    More details BibTeX DOI

    Trautmann, H., Wagner, T., Naujoks, B., Preuss, M., & Mehnen, J. (2009). Statistical Methods for Convergence Detection of Multi-Objective Evolutionary Algorithms. Evolutionary Computation, Special Issue: Twelve Years of EC Research in Dortmund, 17(4), 493–509.
    More details BibTeX

    Conference Paper

    Naujoks, B., & Trautmann, H. (2009). Online Convergence Detection for Multiobjective Aerodynamic Applications. In Tyrrell, A. (Ed.), Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2009, Trondheim, Norway (pp. 332–339). IEEE Press.
    More details BibTeX

    T., W. H. T., & Naujoks, B. (2009). OCD: Online Convergence Detection for Evolutionary Multi-Objective Algorithms Based on Statistical Testing. In Fonseca, C., & Gandibleux, X. (Eds.), Evolutionary Multi-Criterion Optimization (EMO 2009), Lecture Notes in Computer Science (LNCS) 5467 (pp. 198–215). Springer, Berlin.
    More details BibTeX

    Trautmann, H., Mehnen, J., & Naujoks, B. (2009). Pareto-Dominance in Noisy Environments. In Tyrrell, A. (Ed.), Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2009, Trondheim, Norway (pp. 3119–3126). IEEE Press.
    More details BibTeX

  • 2008

    Conference Paper

    Mehnen, J., & Trautmann, H. (2008). Robust Multi-objective Optimisation of Weld Bead Geometry for Additive Manufacturing. In Teti, R. (Ed.), Proceedings of the 6th CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (CIRP ICME '08). Naples, Italy: Copyright C.O.C. Com. org. Conv.
    More details BibTeX

    Trautmann, H., Ligges, U., Mehnen, J., & Preuss, M. (2008). A Convergence Criterion for Multiobjective Evolutionary Algorithms Based on Systematic Statistical Testing. In Rudolph, G., & others, (Eds.), Parallel Problem Solving from Nature (PPSN) (pp. 825–836). Springer, Berlin.
    More details BibTeX

  • 2007

    Conference Paper

    Mehnen, J., Trautmann, H., & Tiwari, A. (2007). Introducing User Preference Using Desirability Functions in Multi-Objective Evolutionary Optimisation of Noisy Processes. In CEC 2007, IEEE Congress on Evolutionary Computation, 2687–2694.
    More details BibTeX

    Weihs, C., & Trautmann, H. (2007). Parallel Universes: Multi-Criteria Optimization. In Berthold, M., Morik, K., & Siebes, A. (Eds.), Dagstuhl Seminar Proceedings 07181, Parallel Universes and Local Patterns. Schloss Dagstuhl, Germany: Internationales Begegnungs- und Forschungszentrum f�r Informatik (IBFI).
    More details BibTeX

  • 2006

    Article in Journal

    Trautmann, H., & Weihs, C. (2006). On the Distribution of the Desirability Index using Harrington's Desirability Function. Metrika, 63(2), 207–213.
    More details BibTeX DOI

    Conference Paper

    Mehnen, J., & Trautmann, H. (2006). Integration of Expert's Preferences in Pareto Optimization by Desirability Function Techniques. In Teti, R. (Ed.), CIRP ICME '06) — Proceedings of the 5th CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (pp. 293–298). Ischia, Italy: C.O.C. Com. org. Conv. CIRP ICME '06.
    More details BibTeX

  • 2004

    Thesis

    Trautmann, H. (2004). Qualitätskontrolle in der Industrie anhand von Kontrollkarten für Wünschbarkeitsindizes — Anwendungsfeld Lagerverwaltung. at the Universität Dortmund.
    More details BibTeX Full text