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Evolutionary Algorithms and Matroid Optimization Problems

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Abstract

We analyze the performance of evolutionary algorithms on various matroid optimization problems that encompass a vast number of efficiently solvable as well as NP-hard combinatorial optimization problems (including many well-known examples such as minimum spanning tree and maximum bipartite matching). We obtain very promising bounds on the expected running time and quality of the computed solution. Our results establish a better theoretical understanding of why randomized search heuristics yield empirically good results for many real-world optimization problems.

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Authors and Affiliations

  1. TU Berlin, Berlin, Germany

    Joachim Reichel & Martin Skutella

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  1. Joachim Reichel
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  2. Martin Skutella
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Correspondence to Joachim Reichel.

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This work was supported by the Deutsche Forschungsgemeinschaft (DFG) as part of the Collaborative Research Center “Computational Intelligence” (SFB 531).

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Reichel, J., Skutella, M. Evolutionary Algorithms and Matroid Optimization Problems. Algorithmica 57, 187–206 (2010). https://doi.org/10.1007/s00453-008-9253-4

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