Wireless sensor networks still face the challenge of energy consumption since sensor nodes carry limited energy, which defines network lifespan. To overcome this, the present research introduces the Tasmanian Devil Optimization Algorithm (TDOA), which is a new metaheuristic algorithm based on the behavior of Tasmanian devils for energy-conscious clustering and routing. TDOA enhances cluster head (CH) selection and route establishment by considering a multi-objective fitness function, including residual energy, trust, security, delay, and transmission distance. The results of the simulation establish the improved performance of TDOA over BOA, BSA, GA, and TSGWO. Compared to BOA, BSA, TDOA showed a 25% decrease in delay, a 20% decrease in average transmission range, 15% enhanced energy efficiency with a 22% enhancement of network life cycle. In these results, TDOA is also presented as an algorithm that can optimize energy utilization, improve routing dependability through trust and security, and modify its performance based on the current state of the network. The study thus validates TDOA as efficient and flexible system for WSNs especially in dynamic and real-time application.