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Bumblebees: a multiagent combinatorial optimization algorithm inspired by social insect behaviour
Comellas Padró, Francesc de Paula; Martínez Navarro, Jesús
Universitat Politècnica de Catalunya. Departament de Matemàtica Aplicada IV
This paper introduces a multiagent optimization algorithm inspired by the collective behavior of social insects. In our method, each agent encodes a possible solution of the problem to solve, and evolves in a way similar to real life insects. We test the algorithm on a classical difficult problem, the $k$-coloring of a graph, and we compare its performance in relation to a standard genetic algorithm and another multiagentsystem. The results show that this algorithmis faster and outperforms the other methods for a range of random graphs with different orders and densities. Moreover, the method is easy to adapt to solve different NP-complete problems.
2012-05-10
Àrees temàtiques de la UPC::Matemàtiques i estadística
Combinatorics
Algorithms
evolutionary algorithm
k-coloring
graphs
bumblebees
Combinacions (Matemàtica)
Algorismes
Classificació AMS::05 Combinatorics
Classificació AMS::68 Computer science::68W Algorithms
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