On the origin of power laws in Internet topologies
ACM SIGCOMM Computer Communication Review
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolving neural networks through augmenting topologies
Evolutionary Computation
Heuristically Optimized Trade-Offs: A New Paradigm for Power Laws in the Internet
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Using PageRank to Characterize Web Structure
COCOON '02 Proceedings of the 8th Annual International Conference on Computing and Combinatorics
Graph Multidrawing: Finding Nice Drawings Without Defining Nice
GD '98 Proceedings of the 6th International Symposium on Graph Drawing
Generating Graphs for Visual Analytics through Interactive Sketching
IEEE Transactions on Visualization and Computer Graphics
Synthetic Generation of High-Dimensional Datasets
IEEE Transactions on Visualization and Computer Graphics
IEEE Communications Magazine
Routing of multipoint connections
IEEE Journal on Selected Areas in Communications
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This paper introduces an interactive system called GraphCuisine that lets users steer an Evolutionary Algorithm (EA) to create random graphs that match user-specified measures. Generating random graphs with particular characteristics is crucial for evaluating graph algorithms, layouts and visualization techniques. Current random graph generators provide limited control of the final characteristics of the graphs they generate. The situation is even harder when one wants to generate random graphs similar to a given one, all-in-all leading to a long iterative process that involves several steps of random graph generation, parameter changes, and visual inspection. Our system follows an approach based on interactive evolutionary computation. Fitting generator parameters to create graphs with pre-defined measures is an optimization problem, while assessing the quality of the resulting graphs often involves human subjective judgment. In this paper we describe the graph generation process from a user's perspective, provide details about our evolutionary algorithm, and demonstrate how GraphCuisine is employed to generate graphs that mimic a given real-world network. An interactive demo of GraphCuisine can be found on our website http://www.aviz.fr/Research/Graphcuisine.