A Network densification is understood as a critical process in the development of cellular networks because to the exponentially rising demands of mobile data traffic. One possible technology to fulfil the requirements of exploding data traffic in 5G is the Ultra-dense heterogeneous network (UDHN). 5G networks of the future will feature dense networks that can deliver high data rates in crowded urban areas. As a result, in heterogeneous networks, the amount of interference and the number of handovers (HOs) increases as more small cells are deployed. In this case, mobility management is critical to ensure that the user's communication is uninterrupted while they travel between cells. Kinetic Gas Molecular Optimization (KGMO) and Ant Lion Optimizatio (ALO) are presented in this study as a hybrid optimization-based mobility management strategy for enhancing network performance Initially, the particles of the KGMO such as position and velocity of the gas molecule are calculated based on the kinetic energy. However, KGMO offers faster convergence in large dimensional space and this leads to the hybridization of KGMO. To overcome this issues of KGMO, ALO is used by modifying the inertia weight of KGMO. The simulation setup of proposed KGMO-ALO is done in MATLAB environment and validated with other popular meta-heuristic techniques such as Seagull and monarch butterfly optimizations in terms of throughput, Bit error rate, end-to-end delay and HO.