Tabu search with graph reduction for finding maximum balanced bicliques in bipartite graphs

Autor: Jin-Kao Hao, Yi Zhou
Přispěvatelé: University of Electronic Science and Technology of China (UESTC), Laboratoire d'Etudes et de Recherche en Informatique d'Angers (LERIA), Université d'Angers (UA), Institut Universitaire de France (IUF), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence, Elsevier, 2019, 77, pp.86-97. ⟨10.1016/j.engappai.2018.09.017⟩
ISSN: 0952-1976
DOI: 10.1016/j.engappai.2018.09.017⟩
Popis: International audience; The Maximum Balanced Biclique Problem is a relevant graph model with a number of applications in diverse domains. However, the problem is NP-hard and thus computationally challenging. In this paper, we introduce a novelmetaheuristic algorithm, which combines an effective constraint-basedtabu searchprocedure and two dedicated graph reduction techniques. We verify the effectiveness of the algorithm on 30 classical random benchmark graphs and 25 very large real-life sparse graphs from the popular Koblenz Network Collection (KONECT). The results show that the algorithm improves the best-known results (new lower bounds) for 10 classical benchmarks and obtains the optimal solutions for 14 KONECT instances.
Databáze: OpenAIRE