EvoGeneS, a new evolutionary approach to graph generation

Authors:
Luigi Pietro Cordella;Claudio De Stefano;Francesco Fontanella;Angelo Marcelli
Affiliations:
Department of Information Engineering and Systems, University of Naples, Naples, Italy;Department of Automation, Electromagnetism, Information Engineering and Industrial Mathematics, University of Cassino, Cassino (FR), Italy;Department of Information Engineering and Systems, University of Naples, Naples, Italy;Department of Computer Science and Electrical Engineering, University of Salerno, Fisciano (SA), Italy
Venue:
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
Year:
2005

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Abstract

Graphs are powerful and versatile data structures, useful to represent complex and structured information of interest in various fields of science and engineering. We present a system, called EvoGeneS, based on an evolutionary approach, for generating undirected graphs whose number of nodes is not a priori known. The method is based on a special data structure, called multilist, which encodes undirected attributed relational graphs. Two novel crossover and mutation operators are defined in order to evolve such structure. The developed system has been tested on a wireless network configuration and the results compared with those obtained by a genetic programming based approach recently proposed in the literature.