High speed of vehicles in vehicular ad hoc network (VANET) makes the dissemination of information from source to destination a very challenging task. The moving vehicles share a predefined road layout, therefore data packets are needed to forward within a particular geographical region only. The geographical region so identified is known as geocast region. Many authors have investigated geocast routing protocols in VANET to ensure effective and efficient transmission of information to a geocast region. The existing geocast routing protocols have limited success due to highly dynamic characteristics of vehicular network and suffer from number of limitations such as scalability and overhead for routing. To reduce and overcome these problems some bio-inspired soft computing techniques have been developed to route the information from source to destination in an optimize manner. In this paper, we have developed and analyzed three geocast routing protocols using particle swarm optimization (PSO) approach named as LARgeoOPT, DREAMgeoOPT, and ZRPgeoOP.

车辆自组织网络（VANET）中车辆的高速行驶使信息从源头到目的地的传播成为一项非常艰巨的任务。移动的车辆共享预定义的道路布局，因此仅在特定地理区域内需要转发数据包。这样确定的地理区域称为地理广播区域。许多作者研究了VANET中的地理广播路由协议，以确保将信息有效且高效地传输到地理广播区域。现有的地理广播路由协议由于车载网络的高度动态特性而获得的成功有限，并且遭受诸如路由的可伸缩性和开销之类的许多限制。为了减少和克服这些问题，已经开发了一些受生物启发的软计算技术，以优化方式将信息从源路由到目的地。在本文中，我们使用粒子群优化（PSO）方法开发并分析了三种地理广播路由协议，分别称为LARgeoOPT，DREAMgeoOPT和ZRPgeoOP。