## 6 Routing Parameter Optimization  
A dedicated cellular multi-objective genetic algorithm has been used to optimize the Metropolitan MANET broadcast technique. The article focuses primarily on MANETs in their entirety and does not primarily reflect on vehicles [54]. [PERSON] and [PERSON] [55] used GA for the management of the multicast transmission problem in MANETs. However, [56] created new routing algorithms for MANETs that are based on ACO considering its authoritative layout. The calculation of PSO was used to cope with scheme resources [57]. The standard OLSR [58] method was used to select a path depending on the link's accessibility. This scheme, however, has several shortcomings in terms of complete resource use and distribution to determine the longest route based on the number of hops. In [59], the authors evaluated the efficiency of two progressive transmissions based on network funds and reduced the time limit. It provides precise neighbor information even if distinct constant bit rate (CBR) sizes are used. When there is a dependency on time synchronization between the traffic source and destination and the connection is used to carry traffic at a consistent bit rate, this service type is employed. In [60], the authors considered adjusting routing parameters so that each node could intermittently trade data. This adjustment was powerful, and the routing panel was rapidly determined, but it was more suitable for less vibrant topology.  
Likewise, QoS readings in reaction moment and message failure were ensured by [61]. QoS also allowed the use of mobile devices to enhance the strength of the connection. [PERSON] et al. [62; 63] provided a helpful evaluation with some obstacles and specifications; QoS was used to upgrade OLSR parameters in packet errors and PDR by reducing the refresh period interval. Tuning routing parameters is the main problem for efficient upgrades between adjacent nodes and promotes stronger road exploration choices under highly vibrant circumstances. The aim of adjusting routing protocol layout parameters is to enhance routing ability and adjust them to realistic circumstances. Identifying defective paths and upgrading the protocol repair process are also the main objectives of enhancement. [PERSON] et al. [64] studied and linked four car tracking algorithms to choose the best algorithm for a variety of transport circumstances at distinct adaptability rates (e.g., travel duration and traffic burden). It will likely offer both road executives and commentators a significant link. [PERSON] et al. [65] proved the use of a time-dependent milestone graph and rider understanding of vibrant road models. They are planning to execute a two-phase calculation for all purposes and find the shortest way to the target at arrival. A clustering method based on entropy differences is used to assess the allocation of travel time. [PERSON] et al. [66] showed a smart path metric. FA-OLSR consolidates a certain number of parameters and relies on fugitive logic.  
Methodologies for scheduling optimization in VANET have used evolutionary algorithms, as shown in [67; 68; 69], such as ACO and PSO. Most of these methods are used to enhance methods with the highest performance feature, which results in a decreased drop in packets, energy, and extended network life. However, the impediments of these approaches are that the route is enhanced based on just two capability features: hop numbers and route performance. Table 2 shows the evolutionary algorithms used for VANET routing and their various categories, objectives, and performance metrics. In short, the primary goal of this work is to characterize the highest parameter scores in distinct VANET circumstances for the routing protocol. Certain characteristics are obtained through the detection of the optimal moment to adjust configuration, particularly concerning load and error.