An evolutionary graph transformation system as a modelling framework for evolutionary algorithms

Authors:
Hauke Tönnies
Affiliations:
University of Bremen, Department of Computer Science, Bremen, Germany
Venue:
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
Year:
2009

Citing 2
Cited 1

Handbook of graph grammars and computing by graph transformation: vol. 2: applications, languages, and tools

Handbook of graph grammars and computing by graph transformation: vol. 2: applications, languages, and tools
Multi-Objective Optimization Using Evolutionary Algorithms

Multi-Objective Optimization Using Evolutionary Algorithms

Autonomous units and their semantics - the concurrent case

Graph transformations and model-driven engineering

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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.