Abstract
In this paper an heuristic method for the solving of complex optimization problems is presented which is inspired equally by genetic algorithms and graph transformation. In short it can be described as a genetic algorithm where the individuals (encoding solutions of the given problem) are always graphs and the operators to create new individuals are provided by graph transformation. As a case study this method is used to solve the independent set problem.
The author would like to acknowledge that his research is partially supported by the Collaborative Research Centre 637 (Autonomous Cooperating Logistic Processes: A Paradigm Shift and Its Limitations) funded by the German Research Foundation (DFG).
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Tönnies, H. (2009). An Evolutionary Graph Transformation System as a Modelling Framework for Evolutionary Algorithms. In: Mertsching, B., Hund, M., Aziz, Z. (eds) KI 2009: Advances in Artificial Intelligence. KI 2009. Lecture Notes in Computer Science(), vol 5803. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04617-9_26
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DOI: https://doi.org/10.1007/978-3-642-04617-9_26
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