@InProceedings{10.1007/978-3-030-03493-1_33,
author="Michalak, Krzysztof",
editor="Yin, Hujun and Camacho, David and Novais, Paulo and Tall{\'o}n-Ballesteros, Antonio J.",
title="Crossover Operator Using Knowledge Transfer for the Firefighter Problem",
booktitle="Intelligent Data Engineering and Automated Learning -- IDEAL 2018",
year="2018",
publisher="Springer International Publishing",
address="Cham",
pages="305--316",
abstract="This paper concerns the Firefighter Problem (FFP) which is a graph-based problem in which solutions can be represented as permutations. A new crossover operator is proposed that uses a machine learning model to decide how to combine two parent solutions of the FFP into an offspring. The operator works on two parent permutations and the machine learning model provides information which parent to select the next permutation element from, when constructing a new solution. Training data is collected during a training run in which transpositions are applied to solutions found by an evolutionary algorithm for a small problem instance. The machine learning model is trained to classify pairs of graph vertices into two classes corresponding to which vertex should be placed earlier in the permutation.",
isbn="978-3-030-03493-1"
}