Graph theory and its applications
Graph theory and its applications
Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Programming III: Darwinian Invention & Problem Solving
Network random keys: a tree representation scheme for genetic and evolutionary algorithms
Evolutionary Computation
Proceedings of the 4th International Workshop on Visual Form
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
Matching Hierarchical Structures Using Association Graphs
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Linear-Graph GP - A New GP Structure
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
Graph-based handwritten digit string recognition
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
Node-depth encoding for evolutionary algorithms applied to multi-vehicle routing problem
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Error thresholds in genetic algorithms
Evolutionary Computation
Graph structured program evolution
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Geometric crossovers for multiway graph partitioning
Evolutionary Computation
Self Modifying Cartesian Genetic Programming: Fibonacci, Squares, Regression and Summing
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
On the bias and performance of the edge-set encoding
IEEE Transactions on Evolutionary Computation
Nonlinear network optimization: an embedding vector space approach
IEEE Transactions on Evolutionary Computation
EvoGeneS, a new evolutionary approach to graph generation
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
Automated synthesis of analog electrical circuits by means ofgenetic programming
IEEE Transactions on Evolutionary Computation
Evolving an expert checkers playing program without using humanexpertise
IEEE Transactions on Evolutionary Computation
Graph-based evolutionary design of arithmetic circuits
IEEE Transactions on Evolutionary Computation
Edge sets: an effective evolutionary coding of spanning trees
IEEE Transactions on Evolutionary Computation
The Automatic Acquisition, Evolution and Reuse of Modules in Cartesian Genetic Programming
IEEE Transactions on Evolutionary Computation
A study of evolutionary multiagent models based on symbiosis
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A new evolutionary system for evolving artificial neural networks
IEEE Transactions on Neural Networks
Genetic evolution of the topology and weight distribution of neural networks
IEEE Transactions on Neural Networks
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Graphs are widely used to represent complex and structured information of interest in various fields of science and engineering. When using graph representations, problems of special interest often imply searching. For example, searching for the prototypes representing a dataset of graphs or for the graph that optimizes a set of parameters. In any case, it is necessary that the problem solution be expressed in terms of graphs. Therefore, defining effective methods for automatically generating single graphs, or sets of graphs, representing problem solutions, is a key issue. A new evolutionary computation-based approach specifically devised for generating graphs is presented. The method is based on a special data structure, called multilist, which allows the encoding of any type of graph, directed or undirected, with or without attributes. Graph encoding by multilists makes it possible to define effective crossover and mutation operators, overcoming the problems normally encountered when implementing genetic operators on graphs. Further advantages of the proposed approach are that it does not require any problem specific knowledge and it is able to search for graphs whose number of nodes is not known a priori. Three sets of experiments were performed to test the proposed approach and the solutions found were compared with those obtained by other approaches proposed in the literature.