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A Relation-Algebraic View on Evolutionary Algorithms for Some Graph Problems

  • Britta Kehden
  • Frank Neumann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3906)

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.

Keywords

Evolutionary Algorithm Random Graph Crossover Operator Vertex Cover Relational Algebra 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Britta Kehden
    • 1
  • Frank Neumann
    • 1
  1. 1.Inst. für Informatik und Prakt. MathematikChristian-Albrechts-Univ. zu KielKielGermany

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