标题： 面向车联网中智能通信的并行多目标元启发式算法 显示英文标题

标题： Parallel multi-objective metaheuristics for smart communications in vehicular networks

摘要： 本文分析了两种并行多目标软计算算法在车载网络中自动搜索自适应按需距离向量路由协议高质量设置的应用。 这些方法基于进化算法和群体智能方法。 实验分析表明，我们的优化算法计算出的配置优于其他最先进的优化配置。 相反，所有并行版本实现的计算效率超过87%。 因此，本文提出的工作路线代表了一个高效的框架来改进车载通信。 显示英文摘要

摘要： 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.