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Iterated Local Search with Guided Mutation

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2 Author(s)
Qingfu Zhang ; Department of Computer Science, University of Essex, Colchester, Wivenhoe Park, CO4 3SQ, UK. ; Jianyong Sun

Guided mutation uses the idea of estimation of distribution algorithms to improve conventional mutation operators. It combines global statistical information and the location information of good individual solutions for generating new trial solutions. This paper suggests using guided mutation in iterative local search. An experimental comparison between a conventional iterated local search (CILS) and an iterated local search with guided mutation has been conducted on four classes of the test instances of the quadratic assignment problem.

Published in:

2006 IEEE International Conference on Evolutionary Computation

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