• 2019

    Conference Paper

    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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  • 2018

    Article in Journal

    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)
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    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.
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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)
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    Book (Monography)

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

    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

    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.
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    Conference Paper

    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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    Chapter in Book

    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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    Report

    Grimme, C., Frischlich, L., Preuß, M., Assenmacher, D., Adam, L., Trautmann, H., & Quandt, T. (2017). Projekt 345: Validierung der automatisierten Erkennung von Social Bots. Bundesamt für Sicherheit in der Informationstechnik. (Accepted)
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  • 2016

    Article in Journal

    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.
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    Conference Paper

    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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  • 2015

    Conference Paper

    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 / 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.
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    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.
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  • 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.
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    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.
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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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  • 2013

    Article in Journal

    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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    Chapter in Book

    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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  • 2012

    Article in Journal

    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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    Chapter in Book

    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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    Thesis

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

    Article in Journal

    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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    Conference Paper

    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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  • 2010

    Article in Journal

    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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    Conference Paper

    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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  • 2009

    Article in Journal

    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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    Conference Paper

    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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  • 2008

    Conference Paper

    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

    Conference Paper

    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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    Report

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

    Conference Paper

    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

    Report

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