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Ant-Based Crossover for Permutation Problems
Jürgen Branke, Christiane Barz, and Ivesa Behrens
Institute AIFB,
University of Karlsruhe,
76128 Karlsruhe, Germany
branke@aifb.uni-karlsruhe.de
Abstract. Crossover for evolutionary algorithms applied to permutation problems is a difficult and widely discussed topic. In this paper we use ideas from ant colony optimization to design a new permutation crossover operator. One of the advantages of the new crossover operator is the ease to introduce problem specific heuristic knowledge. Empirical tests on a travelling salesperson problem show that the new crossover operator yields excellent results and significantly outperforms evolutionary algorithms with edge recombination operator as well as pure ant colony optimization.
LNCS 2723, p. 754 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003