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https://hdl.handle.net/2440/66752
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Type: | Conference paper |
Title: | A Relation-Algebraic View on Evolutionary Algorithms for Some Graph Problems |
Author: | Kehden, B. Neumann, F. |
Citation: | Evolutionary Computation in Combinatorial Optimization: 6th European Conference, EvoCOP 2006, Budapest, Hungary, April 10-12, 2006: Proceedings / J. Gottlieb, G. R. Raidle (eds.), pp.147-158 |
Publisher: | Springer-Verlag Berlin |
Publisher Place: | Heidelberger Platz 3 Berlin Germany D-14197 |
Issue Date: | 2006 |
Series/Report no.: | Lecture Notes in Computer Science |
ISBN: | 3540331786 9783540331780 |
ISSN: | 0302-9743 1611-3349 |
Conference Name: | Evolutionary Computation in Combinatorial Optimization (6th : 2006 : Budapest, Hungary) |
Editor: | Gottlieb, J. Raidl, G.R. |
Statement of Responsibility: | Britta Kehden and Frank Neumann |
Abstract: | We take a relation-algebraic view on the formulation of evolutionary algorithms in discrete search spaces. First, we show how individuals and populations can be represented as relations and formulate some standard mutation and crossover operators for this representation using relation-algebra. Evaluating a population with respect to their constraints seems to be the most costly step in one generation for many important problems. We show that the evaluation process for a given population can be sped up by using relation-algebraic expressions in the process. This is done by examining the evaluation of possible solutions for three of the best-known NP-hard combinatorial optimization problems on graphs, namely the vertex cover problem, the computation of maximum cliques, and the determination of a maximum independent set. Extending the evaluation process for a given population to the evaluation of the whole search space we get exact methods for the considered problems, which allow to evaluate the quality of solutions obtained by evolutionary algorithms. |
Rights: | © Springer-Verlag Berlin Heidelberg 2006 |
DOI: | 10.1007/11730095 |
Published version: | https://doi.org/10.1007/11730095 |
Appears in Collections: | Aurora harvest Computer Science publications |
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