• 2023

    Forschungsartikel in Sammelband (Konferenz)

    Klapproth, J., Unger, S., Pohl, J., Boberg, S., Grimme, C., & Quandt, T. (2023). Immunize the Public against Disinformation Campaigns: Developing a Framework for Analyzing the Macrosocial Effects of Prebunking Interventions. In Proceedings of the Hawaii International Conference on System Sciences (HICSS), Hawaii, HI, 1–10. (accepted / in press (not yet published))
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  • 2022

    Forschungsartikel in Sammelband (Konferenz)

    Grimme, C., Pohl, J., Cresci, S., Lüling, R., & Preuss, M. (2022). New Automation for Social Bots: From Trivial Behavior to AI-Powered Communication. In Spezzano, F., Amaral, A., Ceolin, D., Fazio, L., & Serra, E. (Eds.), Proceedings of the 4th Multidisciplinary International Symposium on Disinformation in Open Online Media (MISDOOM) (1st ed., pp. 79–99). Lecture Notes in Computer Science: Vol. 4. Cham, Switzerland: Springer Nature Switzerland AG.
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    Pohl, J. S., Assenmacher, D., Seiler, M. V., Trautmann, H., & Grimme, C. (2022). Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches. In Association, f. t. A. o. A. I. (. (Ed.), Proceedings of the 16th International Conference on Web and Social Media — 1st Workshop on Novel Evaluation Approaches for Text Classification Systems on Social Media (NEATCLasS) (pp. 1–10). Palo Alto, CA, USA: AAAI Press.
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    Rook, J., Trautmann, H., Bossek, J., & Grimme, C. (2022). On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. In Fieldsend, J., & Wagner, M. (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 356–359-356–359). GECCO '22. New York, NY, USA: Association for Computing Machinery.
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    Forschungsartikel (Zeitschrift)

    Aspar, P., Steinhoff, V., Schäpermeier, L., Kerschke, P., Trautmann, H., & Kerschke, P. (2022). The objective that freed me: a multi-objective local search approach for continuous single-objective optimization. Natural Computing, 1, 1–15.
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    Schäpermeier, L., Grimme, C., & Kerschke, P. (2022). Plotting Impossible? Surveying Visualization Methods for Continuous Multi-Objective Benchmark Problems. IEEE Transactions on Evolutionary Computation. (accepted / in press (not yet published))
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    Abstract in Sammelband (Konferenz)

    Leszkiewicz, A., Bucur, D., Grimme, C., Michalski, R., Clever, L., Pohl, J. S., Rook, J., Bossek, J., Preuss, M., Squillero, G., Quer, S., Calabrese, A., Iacca, G., Kizgin, H., & Trautmann, H. (2022). Social Influence Analysis (SIA) in Online Social Networks. (accepted / in press (not yet published))
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    Forschungsartikel (ePaper)

    Pohl, J. S., Seiler, M. V., Assenmacher, D., & Grimme, C. (2022). A Twitter Streaming Dataset collected before and after the Onset of the War between Russia and Ukraine in 2022.
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  • 2021

    Forschungsartikel in Sammelband (Konferenz)

    Aspar, P., Kerschke, P., Steinhoff, V., Trautmann, H., & Grimme, C. (2021). Multi^3: Optimizing Multimodal Single-Objective Continuous Problems in the Multi-Objective Space by Means of Multiobjectivization. In Ishibuchi, H. e. a. (Ed.), Evolutionary Multi-Criterion Optimization: 11th International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings (pp. 311–322). Heidelberg, Berlin: Springer-Verlag.
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    Markmann, S., & Grimme, C. (2021). Is YouTube Still a Radicalizer? An Exploratory Study on Autoplay and Recommendation. In Proceedings of the Multidisciplinary International Symposium on Disinformation in Open Online Media (MISDOOM), Oxford, UK, 50–65.
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    Schäpermeier, L., Grimme, C., & Kerschke, P. (2021). To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multi-objective Landscapes. In Proceedings of the 11th International Conference on Evolutionary Multi-Criterion Optimization (EMO), Shenzhen, China, 632–644.
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    Forschungsartikel (Zeitschrift)

    Assenmacher, D., Weber, D., Preuss, M., Calero, V. A., Bradshaw, A., Ross, B., Cresci, S., Trautmann, H., Neumann, F., & Grimme, C. (2021). Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem. Social Science Computer Review, online first.
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    Coombs, C., Stacey, P., Kawalek, P., Simeonova, B., Becker, J., Bergener, K., Carvalho, J. Á., Fantinato, M., Garmann-Johnsen, N. F., Grimme, C., Stein, A., & Trautmann, H. (2021). What Is It About Humanity That We Can’t Give Away To Intelligent Machines? A European Perspective. International Journal of Information Management, 58.
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    Grimme, C., Kerschke, P., Aspar, P., Trautmann, H., Preuss, M., Deutz, A., Wang, H., & Emmerich, M. (2021). Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Computers & Operations Research, 136, 105489.
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  • 2020

    Forschungsartikel (Buchbeitrag)

    Grimme, C. (2020). Künstliche Intelligenz: Begriffsklärungen und technische Einschätzungen als Grundlage für Regulierungsansätze. In Aufderheide, D., & Dabrowski, M. (Eds.), Digitalisierung und Künstliche Intelligenz: Wirtschaftsethische und moralökonomische Perspektiven (pp. 159–169). Volkswirtschaftliche Schriften (VWS): Vol. 574. Berlin: Duncker & Humblot.
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    Forschungsartikel in Sammelband (Konferenz)

    Assenmacher, D., Adam, L., Trautmann, H., & Grimme, C. (2020). Towards Real-Time and Unsupervised Campaign Detection in Social Media. In Proceedings of the Florida Artificial Intelligence Research Society Conference, Florida, USA.
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    Assenmacher, D., Clever, L., Pohl, J., Trautmann, H., & Grimme, C. (2020). A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media. In Meiselwitz, G. (Ed.), International Conference on Human-Computer Interaction (HCII 2020): Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis (pp. 201–214). Cham: Springer International Publishing.
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    Assenmacher, D., & Adam, L. &. F. L. &. T. H. &. G. C. (2020). Inside the tool set of automation: Free social bot code revisited. In Grimme, C., Preuß, M., Takes, F., & Waldherr, A. (Eds.), Disinformation in open online media (pp. 101–114). Lecture Notes in Computer Science. Wiesbaden: Springer.
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    Bossek, J., Grimme, C., Rudolph, G., & Trautmann, H. (2020). Towards Decision Support in Dynamic Bi-Objective Vehicle Routing. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Glasgow, UK, 1–8.
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    Bossek, J., Grimme, C., & Trautmann, H. (2020). Dynamic Bi-Objective Routing of Multiple Vehicles. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '20), Cancun, Mexico, 166–174.
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    Clever, L., Assenmacher, D., Müller, K., Seiler, M. V., Riehle, D. M., Preuss, M., & Grimme, C. (2020). FakeYou! — A Gamified Approach for Building and Evaluating Resilience Against Fake News. In Proceedings of the 2nd Multidisciplinary International Symposium on Disinformation in Open Online Media, Leiden, Netherlands.
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    Schäpermeier, L., Grimme, C., & Kerschke, P. (2020). One PLOT to Show Them All: Visualization of Efficient Sets in Multi-Objective Landscapes. In Proceedings of the 16th International Conference on Parallel Problem Solving from Nature (PPSN XVI), Leiden, The Netherlands, 154–167.
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    Steinhoff, V., Kerschke, P., Aspar, P., Trautmann, H., & Grimme, C. (2020). Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent. In Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, Australia, 2445–2452.
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    Forschungsartikel (Zeitschrift)

    Assenmacher, D., Clever, L., Frischlich, L., Quandt, T., Trautmann, , Heike, , & Grimme, C. (2020). Demystifying social bots: On the intelligence of automated social media actors. Social media — society, 00.
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    Sonstige wissenschaftliche Veröffentlichung

    Steinhoff, V., Kerschke, P., & Grimme, C. (2020). Empirical Study on the Benefits of Multiobjectivization for Solving Single-Objective Problems.
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  • 2019

    Forschungsartikel in Sammelband (Konferenz)

    Bossek, J., & Grimme, C. (2019). Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-Criteria Shortest Path Problems. In Battiti, R., Brunato, M., Kotsireas, I., & Pardalos, P. (Eds.), Learning and Intelligent Optimization (pp. 184–198). Lecture Notes in Computer Science: Vol. 11353. Cham: Springer.
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    Bossek, J., Grimme, C., & Neumann, F. (2019). On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '19), Prague, Czech Republic, 516–523.
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    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.
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    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.
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    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.
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    Forschungsartikel (Zeitschrift)

    Kerschke, P., Wang, H., Preuss, M., Grimme, C., Deutz, A., Trautmann, H., & Emmerich, M. (2019). Search Dynamics on Multimodal Multi-Objective Problems. Evolutionary Computation (ECJ), 27(4), 577–609.
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  • 2018

    Fachbuch (Monographie)

    Grimme, C., & Bossek, J. (2018). Einführung in die Optimierung — Konzepte, Methoden und Anwendungen (1st ed.). Springer Vieweg.
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    Forschungsartikel in Sammelband (Konferenz)

    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.
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    Grimme, C., Assenmacher, D., & Adam, L. (2018). Changing Perspectives: Is it Sufficient to Detect Social Bots?. In Proceedings of the International Conference on Human-Computer Interaction, Las Vegas, United States of America. (accepted / in press (not yet published))
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    Sonstige wissenschaftliche Veröffentlichung

    Frischlich, L., & Grimme, C. (2018). Manipulation im Netz: (Medien-) Pädagogik zwischen Fake Accounts, Social Bots, und Propaganda. Münster: Online Whitepaper.
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  • 2017

    Forschungsartikel (Buchbeitrag)

    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.
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    Forschungsartikel in Sammelband (Konferenz)

    Bossek, J., & Grimme, C. (2017). An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling. In Proceedings of the IEEE Symposium Series on Computational Intelligence, Honolulu, Hawaii.
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    Bossek, J., & Grimme, C. (2017). A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem. In Proceedings of the IEEE Symposium Series on Computational Intelligence, Honolulu, Hawai, 3280–3287.
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    Kerschke, P., & Grimme, C. (2017). An Expedition to Multimodal Multi-Objective Optimization Landscapes. In Proceedings of the 9th International Conference on Evolutionary Multi-Criterion Optimization (EMO), Münster, Germany, 329–343.
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    Lang, M., & Grimme, C. (2017). Towards Standardized and Seamless Integration of Expert Knowledge into Multi-objective Evolutionary Optimization Algorithms. In Proceedings of the Evolutionary Multi-Criterion Optimization, Münster, 375–389.
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    Forschungsartikel (Zeitschrift)

    Grimme, C., Preuss, M., Adam, L., & Trautmann, H. (2017). Social Bots: Human-Like by Means of Human Control?. Big Data, 5(4), 279–293.
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  • 2016

    Forschungsartikel in Sammelband (Konferenz)

    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.
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    Forschungsartikel (Zeitschrift)

    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 (Comput. Optim. Appl.), 64(2), 589–618.
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  • 2015

    Forschungsartikel in Sammelband (Konferenz)

    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.
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    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.
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    Abstract als ePaper (Konferenz)

    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.
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    Sonstige wissenschaftliche Veröffentlichung

    Martí, L., Grimme, C., Kerschke, P., Trautmann, H., & Rudolph, G. (2015). Averaged Hausdorff Approximations of Pareto Fronts based on Multiobjective Estimation of Distribution Algorithms.
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  • 2014

    Forschungsartikel (Buchbeitrag)

    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.
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    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.
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    Forschungsartikel in Sammelband (Konferenz)

    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.
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  • 2013

    Forschungsartikel (Buchbeitrag)

    Grimme, C., Kemmerling, M., & Lepping, J. (2013). On the Integration of Theoretical Single-Objective Scheduling Results for Multi-objective Problems. In Tantar, E., Tantar, A., Bouvry, P., Del, M. P., Legrand, P., Coello, C. C., & Schütze, O. (Eds.), EVOLVE- A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation (pp. 333–363). Studies in Computational Intelligence: Vol. 447. Springer Berlin Heidelberg.
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    Forschungsartikel (Zeitschrift)

    Grimme, C., Lepping, J., & Schwiegelshohn, U. (2013). Multi-criteria scheduling: an agent-based approach for expert knowledge integration. Journal of Scheduling, 16(4), 369–383.
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  • 2012

    Forschungsartikel (Buchbeitrag)

    Grimme, C., & Lepping, J. (2012). An Approach to Instantly Use Single-Objective Results for Multi-objective Evolutionary Combinatorial Optimization. In Hamadi, Y., & Schoenauer, M. (Eds.), Learning and Intelligent Optimization (pp. 396–401). Lecture Notes in Computer Science. Springer Berlin Heidelberg.
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    Forschungsartikel (Zeitschrift)

    Grimme, C., Lepping, J., & Papaspyrou, A. (2012). Parallel Predator-Prey Interaction for Evolutionary Multi-Objective Optimization. Natural Computing, 11(3), 519–533.
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    Qualifikationsschrift (Dissertation, Habilitationsschrift)

    Grimme, C. (2012). Das Räuber-Beute-Modell für die mehrkriterielle Optimierung — Analyse und Anwendung. at the Technische Universität Dortmund.
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  • 2011

    Forschungsartikel in Sammelband (Konferenz)

    Grimme, C., Kemmerling, M., & Lepping, J. (2011). An expertise-guided multi-criteria approach to scheduling problems. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 47–48.
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    Grimme, C., & Lepping, J. (2011). Combining basic heuristics for solving multi-objective scheduling problems. In IEEE Symposium on Computational Intelligence in Scheduling (SCIS), 9–16.
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    Grimme, C., & Lepping, J. (2011). Integrating niching into the predator-prey model using epsilon-constraints. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 109–110.
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    Forschungsartikel (Zeitschrift)

    Fölling, A., Grimme, C., Lepping, J., & Papaspyrou, A. (2011). Connecting Community-Grids by Supporting Job Negotiation with Co-evolutionary Fuzzy-Systems. Soft Computing — A Fusion of Foundations, Methodologies and Applications, 15(12), 2375–2387.
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  • 2010

    Forschungsartikel in Sammelband (Konferenz)

    Fölling, A., Grimme, C., Lepping, J., & Papaspyrou, A. (2010). The Gain of Resource Delegation in Distributed Computing Environments. In Schwiegelshohn, U., & Frachtenberg, E. (Eds.), Proceedings of the 15th Workshop on Job Scheduling Strategies for Parallel Processing (pp. 77–92). Lecture Notes in Computer Science. Atlanta (GA), United States: Springer.
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    Grimme, C., Lepping, J., Moreno, P. J., & Papaspyrou, A. (2010). Applying P2P Strategies to Scheduling in Decentralized Grid Computing Infrastructures. In Proceedings of the Sixth International Workshop on Scheduling and Resource Management for Parallel and Distributed Systems, 295–302.
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    Forschungsartikel (Zeitschrift)

    Fölling, A., Grimme, C., Lepping, J., & Papaspyrou, A. (2010). Robust Load Delegation in Service Grid Environments. IEEE Transactions on Parallel and Distributed Systems, 21(9), 1304–1316.
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  • 2009

    Forschungsartikel in Sammelband (Konferenz)

    Fölling, A., Grimme, C., Lepping, J., & Papaspyrou, A. (2009). Decentralized Grid Scheduling with Evolutionary Fuzzy Systems. In Frachtenberg, E., & Schwiegelshohn, U. (Eds.), Proceedings of the 14th Job Scheduling Strategies for Parallel Processing (pp. 16–36). Lecture Notes in Computer Science: Vol. 5798. Springer.
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    Fölling, A., Grimme, C., Lepping, J., & Papaspyrou, A. (2009). Co-evolving Fuzzy Rule Sets for Job Exchange in Computational Grids. In Proceedings of the International Conference on Fuzzy Systems, Jeju Island, Korea, 1683–1688.
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    Grimme, C., Lepping, J., & Papaspyrou, A. (2009). Adapting to the Habitat: On the Integration of Local Search into the Predator-Prey Model. In Proceedings of the Fifth International Conference on Evolutionary Multi-Criterion Optimization (EMO), 510–524.
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    Forschungsartikel (Zeitschrift)

    Fölling, A., Grimme, C., Lepping, J., Papaspyrou, A., & Schwiegelshohn, U. (2009). Competitive Co-evolutionary Learning of Fuzzy Systems for Job Exchange in Computational Grids. Evolutionary Computation, 17(4), 545–560.
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    Grimme, C., & Papaspyrou, A. (2009). Cooperative Negotiation and Scheduling of Scientific Workflows in the Collaborative Climate Community Data and Processing Grid. Future Generation Computer Systems, 25, 301–307.
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    Plantikow, S., Peter, K., Högqvist, M., Grimme, C., & Papaspyrou, A. (2009). Generalizing the Data Management of Three Community Grids. Future Generation Computer Systems, 25, 281–289.
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  • 2008

    Forschungsartikel in Sammelband (Konferenz)

    Grimme, C., Lepping, J., & Papaspyrou, A. (2008). Prospects of Collaboration between Compute Providers by means of Job Interchange. In Frachtenberg, E., & Schwiegelshohn, U. (Eds.), Proceedings of the 13th Job Scheduling Strategies for Parallel Processing (pp. 132–151). Lecture Notes in Computer Science: Vol. 4942. Springer.
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    Grimme, C., Lepping, J., & Papaspyrou, A. (2008). Benefits of Job Exchange Between Autonomous Sites in Decentralized Computational Grids. In Priol, T., Lefevre, L., & Buyya, R. (Eds.), Proccedings of the 8th IEEE International Symposium on Cluster Computing and the Grid (CCGrid) (pp. 25–32). IEEE Computer Society.
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    Grimme, C., Lepping, J., & Papaspyrou, A. (2008). The Parallel Predator-Prey Model: A Step Towards Practical Application. In Rudolph, G., & others, (Eds.), Proceedings of the 10th International Conference on Parallel Problem Solving From Nature (PPSN X) (pp. 681–690). Lecture Notes in Computer Science: Vol. 5199. Springer.
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    Grimme, C., Lepping, J., & Papaspyrou, A. (2008). Discovering Performance Bounds for Grid Scheduling by using Evolutionary Multiobjective Optimization. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 1491–1498.
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  • 2007

    Forschungsartikel in Sammelband (Konferenz)

    Freitag, S., Grimme, C., Papaspyrou, A., & Schley, L. (2007). On the Applicability of OGSA-BES to D-Grid Community Scheduling Systems. In Proceedings of the German E-Science Conference (GES).
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    Grimme, C., Langhammer, T., Papaspyrou, A., & Schintke, F. (2007). Negotiation-based Choreography of Data-intensive Applications in the C3Grid Project. In Proceedings of the German E-Science Conference (GES).
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    Grimme, C., & Lepping, J. (2007). Designing Multi-Objective Variation Operators Using a Predator-Prey Approach. In Proceedings of the Fourth International Conference on Evolutionary Multi-Criterion Optimization, 21–35.
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    Grimme, C., Lepping, J., & Papaspyrou, A. (2007). Exploring the Behavior of Building Blocks for Multi-Objective Variation Operator Design using Predator-Prey Dynamics. In Thierens, D., & others, (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (pp. 805–812). London: ACM Press.
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    Grimme, C., Lepping, J., & Papaspyrou, A. (2007). Identifying Job Migration Characteristics in Decentralized Grid Scheduling Scenarios. In Zheng, S. (Ed.), Proceedings of the 19th International Conference on Parallel and Distributed Computing and Systems (PDCS) (pp. 124–129). Cambridge (MA), USA: ACTA Press.
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    Arbeitspapier / Working Paper

    Grimme, C., Lepping, J., Papaspyrou, A., Wieder, P., Yahyapour, R., Oleksiak, A., Wäldrich, O., & Ziegler, W. (2007). Towards a standards-based Grid Scheduling Architecture.
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  • 2006

    Forschungsartikel in Sammelband (Konferenz)

    Grimme, C., & Schmitt, K. (2006). Inside a Predator-Prey Model for Multi-Objective Optimization: A Second Study. In H., G. B., & others, (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (pp. 707–714). New York: ACM Press.
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  • 2005

    Arbeitspapier / Working Paper

    Grimme, C. (2005). Räuber-Beute-Systeme für die mehrkriterielle Optimierung.
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