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oai:riuma.uma.es:10630/325672026-02-03T11:08:25Zcom_10630_2254col_10630_37953

Parallel multi-objective metaheuristics for smart communications in vehicular networks. Toutouh-el-Alamin, Jamal Alba-Torres, Enrique Sistemas inteligentes de transporte Programación heurística 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. 2024-09-16T12:19:58Z 2024-09-16T12:19:58Z 2024-09-16T12:19:58Z 2015 journal article Toutouh, J., Alba, E. Parallel multi-objective metaheuristics for smart communications in vehicular networks. Soft Comput 21, 1949–1961 (2017). https://hdl.handle.net/10630/32567 10.1007/s00500-015-1891-2 eng open access Springer Nature