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Genom (evolutionärer Algorithmus) (German Wikipedia)

Analysis of information sources in references of the Wikipedia article "Genom (evolutionärer Algorithmus)" in German language version.

refsWebsite
Global rank German rank
14doi.org
2nd place
3rd place
4springer.com
274th place
152nd place
2ieee.org
652nd place
864th place
2kit.edu
6,505th place
962nd place
2zdb-katalog.de
123rd place
6th place
1acm.org
1,185th place
2,009th place
1arxiv.org
69th place
189th place
1elsevier.com
610th place
521st place
1colostate.edu
3,616th place
8,370th place
1mdpi.com
2,912th place
1,242nd place
1github.com
383rd place
343rd place

acm.org (Global: 1,185th place; German: 2,009th place)

dl.acm.org

  • Rachel Cavill, Steve Smith, Andy Tyrrell: Multi-chromosomal Genetic Programming. In: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation - GECCO '05. ACM Press, Washington DC, USA 2005, ISBN 978-1-59593-010-1, S. 1753–1759, doi:10.1145/1068009.1068300 (acm.org [abgerufen am 17. Februar 2022]).

arxiv.org (Global: 69th place; German: 189th place)

  • Wilfried Jakob: Applying Evolutionary Algorithms Successfully: A Guide Gained from Real-world Applications. Karlsruher Institut für Technologie (KIT), 2021, doi:10.5445/ir/1000135763, arxiv:2107.11300 (kit.edu [abgerufen am 19. Februar 2022]).

colostate.edu (Global: 3,616th place; German: 8,370th place)

cs.colostate.edu

  • Jean-Paul Watson, Darrell Whitley: The GENITOR Group. Colorado State University, USA, abgerufen am 21. Februar 2022.

doi.org (Global: 2nd place; German: 3rd place)

  • Nicholas Baine: A simple multi-chromosome genetic algorithm optimization of a Proportional-plus-Derivative Fuzzy Logic Controller. In: NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society. Mai 2008, S. 1–5, doi:10.1109/NAFIPS.2008.4531273 (ieee.org [abgerufen am 17. Februar 2022]).
  • Jin Peng, Zhang Shu Chu: A Hybrid Multi-chromosome Genetic Algorithm for the Cutting Stock Problem. In: 2010 3rd International Conference on Information Management, Innovation Management and Industrial Engineering. Band 1, November 2010, S. 508–511, doi:10.1109/ICIII.2010.128 (ieee.org [abgerufen am 17. Februar 2022]).
  • Rachel Cavill, Steve Smith, Andy Tyrrell: Multi-chromosomal Genetic Programming. In: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation - GECCO '05. ACM Press, Washington DC, USA 2005, ISBN 978-1-59593-010-1, S. 1753–1759, doi:10.1145/1068009.1068300 (acm.org [abgerufen am 17. Februar 2022]).
  • Wilfried Jakob: Applying Evolutionary Algorithms Successfully: A Guide Gained from Real-world Applications. Karlsruher Institut für Technologie (KIT), 2021, doi:10.5445/ir/1000135763, arxiv:2107.11300 (kit.edu [abgerufen am 19. Februar 2022]).
  • Hartmut Pohlheim: Evolutionäre Algorithmen. Springer Berlin Heidelberg, Berlin, Heidelberg 2000, ISBN 978-3-642-63052-1, doi:10.1007/978-3-642-57137-4 (springer.com [abgerufen am 21. Februar 2022]).
  • Edgar Galván-López, James McDermott, Michael O’Neill, Anthony Brabazon: Towards an Understanding of Locality in Genetic Programming. In: Conf. proc. of Genetic and Evolutionary Computation Conference (GECCO’10). ACM, New York 2010, S. 901–908, doi:10.1145/1830483.1830646.
  • Volker Nissen: Evolutionäre Algorithmen. Deutscher Universitätsverlag, Wiesbaden 1994, ISBN 978-3-8244-0217-5, doi:10.1007/978-3-322-83430-0 (springer.com [abgerufen am 19. Februar 2022]).
  • Darrell Whitley: A Genetic Algorithm Tutorial. In: Statistics and Computing. Band 4, Nr. 2, Juni 1994, ISSN 0960-3174, doi:10.1007/BF00175354 (springer.com [abgerufen am 21. Februar 2022]).
  • F. Herrera, M. Lozano, J.L. Verdegay: Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis. In: Artificial Intelligence Review. Band 12, Nr. 4, 1998, S. 265–319, doi:10.1023/A:1006504901164 (springer.com [abgerufen am 20. Februar 2022]).
  • Darrell Whitley: An overview of evolutionary algorithms: practical issues and common pitfalls. In: Information and Software Technology. Band 43, Nr. 14, Dezember 2001, S. 817–831, doi:10.1016/S0950-5849(01)00188-4 (elsevier.com [abgerufen am 21. Februar 2022]).
  • P. Larrañaga, C.M.H. Kuijpers, R.H. Murga, I. Inza, S. Dizdarevic: Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators. In: Artificial Intelligence Review. Band 13, Nr. 2, 1999, S. 129–170, doi:10.1023/A:1006529012972.
  • A.E. Eiben, J.E. Smith: Introduction to Evolutionary Computing (= Natural Computing Series). Springer, Berlin, Heidelberg 2015, ISBN 978-3-662-44873-1, Permutation Representation, S. 67–74, doi:10.1007/978-3-662-44874-8.
  • Wilfried Jakob, Sylvia Strack, Alexander Quinte, Günther Bengel, Karl-Uwe Stucky: Fast Rescheduling of Multiple Workflows to Constrained Heterogeneous Resources Using Multi-Criteria Memetic Computing. In: Algorithms. Band 6, Nr. 2, 22. April 2013, ISSN 1999-4893, S. 245–277, doi:10.3390/a6020245 (mdpi.com [abgerufen am 21. Februar 2022]).
  • Christian Blume, Wilfried Jakob: GLEAM - General Learning Evolutionary Algorithm and Method : ein Evolutionärer Algorithmus und seine Anwendungen. KIT Scientific Publishing, 2009, doi:10.5445/ksp/1000013553 (kit.edu [abgerufen am 21. Februar 2022]).

elsevier.com (Global: 610th place; German: 521st place)

linkinghub.elsevier.com

  • Darrell Whitley: An overview of evolutionary algorithms: practical issues and common pitfalls. In: Information and Software Technology. Band 43, Nr. 14, Dezember 2001, S. 817–831, doi:10.1016/S0950-5849(01)00188-4 (elsevier.com [abgerufen am 21. Februar 2022]).

github.com (Global: 383rd place; German: 343rd place)

  • Wilfried Jakob: Git-Repository von GLEAM. Karlsruher Institut für Technologie, 2021, abgerufen am 23. Februar 2022 (englisch).

ieee.org (Global: 652nd place; German: 864th place)

ieeexplore.ieee.org

  • Nicholas Baine: A simple multi-chromosome genetic algorithm optimization of a Proportional-plus-Derivative Fuzzy Logic Controller. In: NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society. Mai 2008, S. 1–5, doi:10.1109/NAFIPS.2008.4531273 (ieee.org [abgerufen am 17. Februar 2022]).
  • Jin Peng, Zhang Shu Chu: A Hybrid Multi-chromosome Genetic Algorithm for the Cutting Stock Problem. In: 2010 3rd International Conference on Information Management, Innovation Management and Industrial Engineering. Band 1, November 2010, S. 508–511, doi:10.1109/ICIII.2010.128 (ieee.org [abgerufen am 17. Februar 2022]).

kit.edu (Global: 6,505th place; German: 962nd place)

publikationen.bibliothek.kit.edu

  • Wilfried Jakob: Applying Evolutionary Algorithms Successfully: A Guide Gained from Real-world Applications. Karlsruher Institut für Technologie (KIT), 2021, doi:10.5445/ir/1000135763, arxiv:2107.11300 (kit.edu [abgerufen am 19. Februar 2022]).
  • Christian Blume, Wilfried Jakob: GLEAM - General Learning Evolutionary Algorithm and Method : ein Evolutionärer Algorithmus und seine Anwendungen. KIT Scientific Publishing, 2009, doi:10.5445/ksp/1000013553 (kit.edu [abgerufen am 21. Februar 2022]).

mdpi.com (Global: 2,912th place; German: 1,242nd place)

  • Wilfried Jakob, Sylvia Strack, Alexander Quinte, Günther Bengel, Karl-Uwe Stucky: Fast Rescheduling of Multiple Workflows to Constrained Heterogeneous Resources Using Multi-Criteria Memetic Computing. In: Algorithms. Band 6, Nr. 2, 22. April 2013, ISSN 1999-4893, S. 245–277, doi:10.3390/a6020245 (mdpi.com [abgerufen am 21. Februar 2022]).

springer.com (Global: 274th place; German: 152nd place)

link.springer.com

zdb-katalog.de (Global: 123rd place; German: 6th place)

  • Darrell Whitley: A Genetic Algorithm Tutorial. In: Statistics and Computing. Band 4, Nr. 2, Juni 1994, ISSN 0960-3174, doi:10.1007/BF00175354 (springer.com [abgerufen am 21. Februar 2022]).
  • Wilfried Jakob, Sylvia Strack, Alexander Quinte, Günther Bengel, Karl-Uwe Stucky: Fast Rescheduling of Multiple Workflows to Constrained Heterogeneous Resources Using Multi-Criteria Memetic Computing. In: Algorithms. Band 6, Nr. 2, 22. April 2013, ISSN 1999-4893, S. 245–277, doi:10.3390/a6020245 (mdpi.com [abgerufen am 21. Februar 2022]).