RT Journal Article
T1 Parallel multi-objective metaheuristics for smart communications in vehicular networks.
A1 Toutouh-el-Alamin, Jamal
A1 Alba-Torres, Enrique
K1 Sistemas inteligentes de transporte
K1 Programación heurística
AB This article analyzes the use of two parallel multi-objective soft computing algorithms to automatically search for high-quality settings of the Ad hoc On Demand Vector routing protocol for vehicular networks. These methods are based on an evolutionary algorithm and on a swarm intelligence approach. The experimental analysis demonstrates that the configurations computed by our optimization algorithms outperform other state-of-the-art optimized ones. In turn, the computational efficiency achieved by all the parallel versions is greater than 87 %. Therefore, the line of work presented in this article represents an efficient framework to improve vehicular communications.
PB Springer Nature
YR 2015
FD 2015
LK https://hdl.handle.net/10630/32567
UL https://hdl.handle.net/10630/32567
LA eng
NO Toutouh, J., Alba, E. Parallel multi-objective metaheuristics for smart communications in vehicular networks. Soft Comput 21, 1949–1961 (2017).
NO Política de acceso abierto tomada de: https://v2.sherpa.ac.uk/id/publication/28648
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026