文件列表:

dataset/
ea/
greedy/
output/
paper-figures/comparision/dblp-ho/
random/
single-objective/
summarization/
loaders.py
main.py
moea.py
monte_carlo.py
plot_utils.py
requirements.txt
smart_initialization.py

# Multi-objective Evolutionary Algorithms for Influence Maximization in Hypergraph Networks [\[Report\]](https://github.com/StefanoGenettiUniTN/mo-ea-hypergraph-influence-maximization/blob/master/) The goal of influence maximization (IM) is to reach the maximum number of entities in a network, starting from a small set of seed nodes, and assuming a model for information propagation. While this task has been widely studied in ordinary graph networks, IM in hypergraphs (where hyperedges represent interactions among more than two nodes) has not been adequately explored yet. This study introduces valuable algorithmic solutions to tackle the IM problem in hypergraph networks, including an original method based on hypergraph summarization suited for large-scale networks.

## Requirements Before getting started, make sure you have installed inspyred and hypergraphx. ``` pip install inspyred pip install hypergraphx ``` ## Structure The repository is structured as follows: ``` . ├── dataset # Hypergraphs dataset ├── ea # Files implementing the inspyred functions (evaluator, mutator, ...) ├── greedy # Implementation of the greedy baseline ├── random # Implementation of the random baseline ├── single-objective # Implementation of the single objective optimization algorithm └── summarization # Implementation of the summarization algorithm ``` ## Usage The NSGA-II algorithm can be executed with the follwowing algorithm ```shell python main.py --hypergraph_path ".\dataset\amazon-antelmi\amazon.json" --max_generations 30 --model HO --no_simulations 100 --max_seed_nodes 0.01 --output_file_path "output\moea.json" --output_execution_time_file_path "output\moea.txt" ``` ## Contribution Authors: - Stefano Genetti, MSc Student University of Trento (Italy), stefano.genetti@studenti.unitn.it - Eros Ribaga, MSc Student University of Trento (Italy), eros.ribaga@studenti.unitn.it - Giovanni Iacca, Associate Professor University of Trento (Italy), giovanni.iacca@unitn.it For every type of doubts/questions about the repository please do not hesitate to contact us.

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