FSTDO: a hybrid heuristic-algorithm-based multi-objective function formulation for multipath routing mechanism in MANET

{A Hybrid Heuristic-aided Multi-Objective Functions-based Fitness Sewing Training and Dingo Optimization for Multipath Routing Mechanism in MANET}Mobile Ad Hoc Networks (MANETs) are made up of a group of wireless mobile nodes that dynamically exchange data from one to another. The core aim of the model is to achieve optimal route selection for facilitating a better routing mechanism. The first step is determining the optimal routes between the mobile nodes by using the proposed hybrid Fitness-based Sewing Training and Dingo Optimization (FSTDO). The suggested approach is used to derive the multi-objective functions using the same constraints, such as energy consumption, distance, routing overhead ratio, throughput, end-to-end delay, Packet Delivery Ratio (PDR), link reliability, fault tolerance, and load-balancing based on bandwidth and traffic load distribution. The optimal routes are employed to choose the effective path from source to destination. The findings showed better performance than other routing processes.