MANETs have distinctive routing issues as a result of their dynamic and decentralized characteristics. This research presents a new method for achieving the most efficient routing in Mobile Ad hoc Networks (MANETs) by combining two intelligent optimization algorithms: Ant Colony Optimization (ACO) and Bacterial Foraging Algorithm (BFA). The main objective of this technique is to optimize the weight of the routes. The Weight-Optimized ACO with BFA (WOAB) algorithm utilizes the collective intelligence of ACO to identify possible routes and the exploration-exploitation skills of BFA to improve these routes. The algorithm creates an optimal balance between exploration and exploitation by assigning weights to the paths using both ACO and BFA optimizations. This results in enhanced routing efficiency. Comprehensive simulations and evaluations are performed in several MANET situations, taking into account parameters such as network density, node mobility, and varying communication demands. The findings indicate that WOAB outperforms conventional routing protocols in terms of packet delivery ratio, end-to-end delay, and energy efficiency. The WOAB approach shows potential in solving the issues of finding the best routes in MANETs, making a useful contribution to improving communication reliability and resource usage in dynamic wireless networks.

Optimization, weight, ACO, fitness function, shortest route, BFA, and energy consumption