Vehicular Ad Hoc Network (VANETs)-based cluster creation is a promising research area that works for intelligent transportation systems in the daily technical world. It intends to segment the vehicles that are in the moving condition in some groups called clusters in the roads. Due to high mobility in VANETs, the network energy consumption and overhead increase. Effective CH selection becomes essential to solve the issue and improve VANETs’ firmness. Most of the earlier clustering-based approaches are in the form of a distributed model that leads to reduced effectiveness in the mobility environment. This paper proposes a Hybrid Bio-inspired Optimization-Based Enhanced CH Selection (HBO-ECHS) to improve the communication in VANETs. Hybrid optimization combines the butterfly optimization algorithm (BOA) and ant colony optimization (ACO) algorithm. The main processes of CH selection are cluster formation, hybrid optimization-based CH selection, and position improvisation. The simulation is done using the software NS2. The parameters that are concentrated for performance evaluation are packet delivery ratio, end-to-end delay, energy efficiency, and routing overhead. To perform a comparative analysis, the results of the proposed HBO-ECHS are compared with earlier works, such as AJ-MOFA and RJ-EDCV. The performance evaluation proves that the proposed HBO-ECHS approach achieves a high packet delivery ratio, energy efficiency, and a low end-to-end delay and routing overhead compared with the earlier approaches.