RT dataset
T1 Dataset of the paper “A stepped tabu search method for the clique partitioning problem”. Applied Intelligence, 53, 16275-16292
A1 Pacheco Bonrostro, Joaquín
A1 Casado Yusta, Silvia
K1 Clique partitioning problem
K1 Metaheuristics
K1 Tabu search
K1 Multistart methods
K1 Investigación operativa
K1 Operations research
K1 Modelos matemáticos
K1 Mathematical models
AB Given an undirected graph, a clique is a subset of vertices in which the induced subgraph is complete; that is, all pairs of vertices of this subset are adjacent. Clique problems in graphs are very important due to their numerous applications. One of these problems is the clique partitioning problem (CPP), which consists of dividing the set of vertices of a graph into the smallest number of cliques possible. The CPP is an NP-hard problem with many application fields (timetabling, manufacturing, scheduling, telecommunications, etc.). Despite its great applicability, few recent studies have focused on proposing specific resolution methods for the CPP. This article presents a resolution method that combines multistart strategies with tabu search. The most novel characteristic of our method is that it allows unfeasible solutions to be visited, which facilitates exploration of the solution space. The computational tests show that our method performs better than previous methods proposed for this problem. In fact, our method strictly improves the results of these methods in most of the instances considered while requiring less computation time.
PB Universidad de Burgos
YR 2022
FD 2022
LK http://hdl.handle.net/10259/9822
UL http://hdl.handle.net/10259/9822
LA eng
NO This work was partially supported by FEDER funds and the Spanish State Research Agency (Projects PID2019-104263RB-C44 and PDC2021–121021-C22); the Regional Government of “Castilla y León”, Spain (Project BU071G19); the Regional Government of “Castilla y León”; and FEDER funds (Project BU056P20).
DS Repositorio Institucional de la Universidad de Burgos
RD 22-dic-2024