@inproceedings{67ef5072823e44348d1fc459183f373b,
title = "Using a Social Media Inspired Optimization Algorithm to Solve the Set Covering Problem",
abstract = "Currently, researchers have focused on solving large-scale and non-linear optimization problems. Metaheuristics as its prefix indicates, are superior heuristics that aim to deliver acceptable results to optimization problems in a short period of time, trying to achieve a correct balance between exploration and exploitation in the search for solutions. In this paper we present the application of a metaheuristic technique called Social media optimization algorithm for the resolution of the Set Covering Problem (SCP). This technique is inspired by the behavior of users of social networking platforms such as Twitter. The users through different interactions manage to make a Tweet more relevant than others. The user who generates the best Tweet, is recognized as a celebrity. This process of social relationship is precisely what allows us to find better solutions given the experiments and results presented in this document.",
keywords = "Metaheuristics, SCP, Social media, Twitter Optimization",
author = "Broderick Crawford and Ricardo Soto and Guillermo Cabrera and Agust{\'i}n Salas-Fern{\'a}ndez and Fernando Paredes",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; null ; Conference date: 26-07-2019 Through 31-07-2019",
year = "2019",
doi = "10.1007/978-3-030-21902-4_4",
language = "English",
isbn = "9783030219017",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "43--52",
editor = "Gabriele Meiselwitz",
booktitle = "Social Computing and Social Media. Design, Human Behavior and Analytics - 11th International Conference, SCSM 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings",
}