Edge computing allows mobile device users to offload tasks to maximize battery life as well as minimize latency when applications are being used. Here, we focus on developing a new model that is a blend of the Whale Optimization Algorithm and Artificial Bee Colony (WOA-ABC) aimed at improving effectiveness in Mobile Edge Computing (MEC). The combined method employs the distinct features of WOA to optimize the search process, while refinement extracts the best from the ABC. Its features optimize improvement in resource management, reduce operating costs, lower battery discharges, and minimize latency and energy use as the system becomes more stable. Our simulation results show that the hybrid WOA-ABC is more efficient than the conventional techniques, and this makes it ideal for smart cities and IoT environments where there is a need for mobile edge computing. These aspects of offloading are also effectively addressed, as this approach provides a reliable and flexible solution to real-life MEC settings.