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1625 Publications


2019 | Conference Paper | LibreCat-ID: 46343
C. Grimme, P. Kerschke, and H. Trautmann, “Multimodality in Multi-Objective Optimization — More Boon than Bane?,” in Proceedings of the 10$^th$ International Conference on Evolutionary Multi-Criterion Optimization (EMO), 2019, vol. 11411, pp. 126–138, doi: 10.1007/978-3-030-12598-1_11.
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2019 | Conference Paper | LibreCat-ID: 46342
C. Grimme, P. Kerschke, M. T. M. Emmerich, M. Preuss, A. H. Deutz, and H. Trautmann, “Sliding to the Global Optimum: How to Benefit from Non-Global Optima in Multimodal Multi-Objective Optimization,” in AIP Conference Proceedings, 2019, pp. 020052-1-020052–4, doi: 10.1063/1.5090019.
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2019 | Book Chapter | LibreCat-ID: 48341
M. Wille, “Prinzipien und Strategien der Textgliederung in den Zeitungen des 18. Jahrhunderts – Eine computerbasierte Korpusanalyse,” in Textgliederungsprinzipien. Ihre Kennzeichnungsformen und Funktionen vom 8. bis 18. Jahrhundert. Akten zum Internationalen Kongress vom 22. bis 24. Juni 2017 an der Universität St. Petersburg, vol. 34, F. Simmler and G. Baeva, Eds. Berlin: Weidler, 2019, pp. 507–531.
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2019 | Book Chapter | LibreCat-ID: 31142
B.-M. Schuster, “Textgliederungsprinzipien und Beziehungsgestaltung im Stammbuch von 1559–1878,” in Textgliederungsprinzipien. Ihre Kennzeichnungsformen und Funktionen in Texten vom 8. bis 18. Jahrhundert. Akten zum Internationalen Kongress an der Staatlichen Universität St. Petersburg vom 22. bis 24. Juni 2017, F. Simmler and G. Baeva, Eds. Berlin : WEIDLER, 2019, pp. 293–312.
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2019 | Book Chapter | LibreCat-ID: 46336
P. Kerschke and H. Trautmann, “Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-package flacco,” in Applications in Statistical Computing, N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek, H. Trautmann, and M. Vichi, Eds. Springer, 2019, pp. 93–123.
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2019 | Journal Article | LibreCat-ID: 46346
P. Kerschke and H. Trautmann, “Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning,” Evolutionary Computation (ECJ), vol. 27, no. 1, pp. 99–127, 2019, doi: 10.1162/evco_a_00236.
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2019 | Journal Article | LibreCat-ID: 46347
P. Kerschke et al., “Search Dynamics on Multimodal Multi-Objective Problems,” Evolutionary Computation (ECJ), vol. 27, no. 4, pp. 577–609, 2019, doi: 10.1162/evco_a_00234.
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2019 | Conference Paper | LibreCat-ID: 23720
I. Gräßler, J. Pottebaum, P. Taplick, D. Roesmann, and D. Preuß, “Unterstützung des Lernens für kritische Situationen: Potenzial von Augmented Reality für die Instandsetzung auf See,” in Go-3D 2019 “Mit 3D Richtung Maritim 4.0” - Tagungsband zur Konferenz Go-3D 2019, 2019, pp. 45–57.
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2019 | Conference Paper | LibreCat-ID: 48841
J. Bossek, C. Grimme, S. Meisel, G. Rudolph, and H. Trautmann, “Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm,” in Evolutionary Multi-Criterion Optimization (EMO), 2019, pp. 516–528, doi: 10.1007/978-3-030-12598-1_41.
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2019 | Conference Paper | LibreCat-ID: 48842
J. Bossek, P. Kerschke, A. Neumann, M. Wagner, F. Neumann, and H. Trautmann, “Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators,” in Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2019, pp. 58–71, doi: 10.1145/3299904.3340307.
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2019 | Conference Paper | LibreCat-ID: 48843
J. Bossek, F. Neumann, P. Peng, and D. Sudholt, “Runtime Analysis of Randomized Search Heuristics for Dynamic Graph Coloring,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2019, pp. 1443–1451, doi: 10.1145/3321707.3321792.
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2019 | Conference Paper | LibreCat-ID: 48840
J. Bossek, C. Grimme, and F. Neumann, “On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2019, pp. 516–523, doi: 10.1145/3321707.3321818.
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2019 | Conference Paper | LibreCat-ID: 48858
J. Bossek and C. Grimme, “Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-criteria Shortest Path Problems,” in Learning and Intelligent Optimization, 2019, pp. 184–198, doi: 10.1007/978-3-030-05348-2_17.
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2019 | Conference Paper | LibreCat-ID: 48875
J. Bossek and H. Trautmann, “Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time,” in Learning and Intelligent Optimization, 2019, pp. 215–219, doi: 10.1007/978-3-030-05348-2_19.
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2019 | Conference Paper | LibreCat-ID: 22041
E. Moritzer, A. Hirsch, and F. Hecker, “Process Parameter Optimization to Improve the Mechanical Properties of Arburg Plastic Freeformed Components,” in 30th Annual International Solid Freeform Fabrication Symposium, 2019, vol. 30, pp. 705–714, doi: http://dx.doi.org/10.26153/tsw/17308.
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2019 | Journal Article | LibreCat-ID: 53274
M. Soleymani, I. Santamaria, C. Lameiro, and P. J. Schreier, “Ergodic Rate for Fading Interference Channels with Proper and Improper Gaussian Signaling,” Entropy, vol. 21, no. 10, Art. no. 922, 2019, doi: 10.3390/e21100922.
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2019 | Journal Article | LibreCat-ID: 4684
D. Beverungen, O. Müller, M. Matzner, J. Mendling, and J. vom Brocke, “Conceptualizing smart service systems,” Electronic Markets, vol. 29, pp. 7–18, 2019, doi: 10.1007/s12525-017-0270-5.
LibreCat | Files available | DOI
 

2019 | Journal Article | LibreCat-ID: 53976
S. M. Mousavi, M. Tavana, N. Alikar, and M. Zandieh, “A tuned hybrid intelligent fruit fly optimization algorithm for fuzzy rule generation and classification,” Neural Computing and Applications, vol. 31, no. 3, pp. 873–885, 2019, doi: 10.1007/s00521-017-3115-4.
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2019 | Journal Article | LibreCat-ID: 53974
S. M. Mousavi, N. Alikar, M. Tavana, and D. Di Caprio, “An improved particle swarm optimization model for solving homogeneous discounted series-parallel redundancy allocation problems,” Journal of Intelligent Manufacturing, vol. 30, no. 3, pp. 1175–1194, 2019, doi: 10.1007/s10845-017-1311-9.
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2019 | Journal Article | LibreCat-ID: 53969
V. Hajipour, M. Tavana, D. Di Caprio, M. Akhgar, and Y. Jabbari, “An optimization model for traceable closed-loop supply chain networks,” Applied Mathematical Modelling, vol. 71, pp. 673–699, 2019, doi: 10.1016/j.apm.2019.03.007.
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