In dynamic wireless networks like Mobile Ad Hoc Networks (MANETs), where nodes communicate without a fixed infrastructure, ensuring secure and efficient communication is crucial due to inherent vulnerabilities such as malicious attacks and energy constraints. To address this issue, this study introduces a novel approach that combines Tasmanian Devil Optimization (TDO) and Gazelle Optimization Algorithm (GOA), termed Hybrid Tasmanian Gazelle Optimization (HTGO). This approach is designed to enhance energy-efficient routing and secure communication in MANETs. The HTGO method combines the strengths of local exploration from the TDO and global exploitation from the GOA which increases the overall performance in cluster head selection. The system optimizes routing paths by considering various factors such as energy consumption, communication cost, trust, and network load. Additionally, the study integrates fuzzy logic-based trust evaluation to increase security by detecting malicious nodes during data transmission. The system is implemented and tested on a simulation platform, with performance evaluated using key metrics such as Packet Delivery Ratio (PDR), energy consumption, network lifespan, delay, Packet Loss Ratio (PLR), and detection rate of malicious nodes. Experimental results show that HTGO outperforms existing methods by achieving longer network lifetime, higher PDR, lower energy consumption, and a reduced delay. It also demonstrates superior security with a detection rate of 93% for malicious nodes, highlighting its effectiveness in both energy optimization and secure communication in MANETs. This study contributes to more secure and energy-efficient routing in MANETs, which provides an ideal solution for dynamic and vulnerable wireless network environments.