Parallel multi-objective metaheuristics for smart communications in vehicular networks. - Toutouh-el-Alamin, Jamal; Alba-Torres, Enrique (Springer Nature, 2015)
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.
Política de acceso abierto tomada de: https://v2.sherpa.ac.uk/id/publication/28648
Keywords: Sistemas inteligentes de transporte; Programación heurística; Metaheuristics; Vehicular ad hoc networks; Optimization