H. Grass Boada, J. López Fidalgo, E. Benitez, C. De La Calle Arroyo

In the past decade, there has been an increasing interest in the analysis of complex networks due to their applications in several contexts. In the context of large-scale optimization problems, a innovate class of algorithms developed, the so-called metaheuristics. One of the issues to attend in the metaheuristic algorithms is the need of setting the values of several components and parameters within them.
Design of Experiments is well established theoretically and offers efficiency in terms of the amount of data that needs to be gathered, which is critical when attempting to understand immense algorithm design spaces. Therefore, with the aim to obtain the best performance of the metaheuristic algorithms, a systematic method of tuning up these parameters should be developed. In our case, to analyze the parameter tuning approach in metaheuristics, a Genetic Algorithm is used due to its wide application area, including community detection in complex networks.

Keywords: Community Detection, metaheuristics, Response surface methodology


GT06.DEX1 Invited Session
November 7, 2023  6:40 PM
CC4: Room 2

Other papers in the same session

Diseño óptimo en ensayos de clonogenicidad.

M. J. Rivas Lopez, J. M. Rodríguez Díaz

Cookie policy

We use cookies in order to be able to identify and authenticate you on the website. They are necessary for the correct functioning of it, and therefore they can not be disabled. If you continue browsing the website, you are agreeing with their acceptance, as well as our Privacy Policy.

Additionally, we use Google Analytics in order to analyze the website traffic. They also use cookies and you can accept or refuse them with the buttons below.

You can read more details about our Cookie Policy and our Privacy Policy.