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https://hdl.handle.net/2440/66826
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Type: | Conference paper |
Title: | Evolutionary algorithms and dynamic programming |
Author: | Doerr, B. Eremeev, A. Horoba, C. Neumann, F. Theile, M. |
Citation: | Proceedings of the 11th Annual conference on Genetic and Evolutionary Computation: GECCO '09, pp.771-777 |
Publisher: | ACM Press |
Publisher Place: | New York |
Issue Date: | 2009 |
ISBN: | 9781605583259 |
Conference Name: | Genetic and Evolutionary Computation Conference (11th : 2009 : Montreal, Canada) |
Editor: | Rothlauf, F. |
Statement of Responsibility: | Benjamin Doerr, Anton Eremeev, Christian Horoba, Frank Neumann and Madeleing Theile |
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. |
Keywords: | Combinatorial optimization dynamic programming evolutionary algorithms |
Rights: | Copyright 2009 ACM |
DOI: | 10.1145/1569901.1570008 |
Published version: | http://dx.doi.org/10.1145/1569901.1570008 |
Appears in Collections: | Aurora harvest 5 Computer Science publications |
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