| Evolutionary algorithms and dynamic programming |
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Genetic And Evolutionary Computation Conference
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Proceedings of the 11th Annual conference on Genetic and evolutionary computation
table of contents
Montreal, Québec, Canada
SESSION: Track 9: genetic algorithms
table of contents
Pages 771-778
Year of Publication: 2009
ISBN:978-1-60558-325-9
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Authors
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Benjamin Doerr
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Max-Planck-Institut für Informatik, Saarbruecken, Germany
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Anton Eremeev
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Omsk Branch of Sobolev Institute of Mathematics, Omsk, Russian Fed.
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Christian Horoba
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TU Dortmund, Dortmund, Germany
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Frank Neumann
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Max-Planck-Institut für Informatik, Saarbruecken, Germany
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Madeleine Theile
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TU Berlin, Berlin, Germany
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ABSTRACT
Recently, it has been proven that evolutionary algorithms produce good results for a wide range of combinatorial optimization problems. Some of the considered problems are tackled by evolutionary algorithms that use a representation, which enables them to construct solutions in a dynamic programming fashion. We take a general approach and relate the construction of such algorithms to the development of algorithms using dynamic programming techniques. Thereby, we give general guidelines on how to develop evolutionary algorithms that have the additional ability of carrying out dynamic programming steps.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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