Long term evolution (LTE) is a leading mobile technology that provides very high speeds, low latency, and better quality-of-service (QoS). However, because of the exponential growth in the number of mobile users, the variety of new handheld devices, and the incremental use of different applications, the core network experiences a significant signaling overhead. This demand requires the design of intelligent, optimized mobility management methods. The present work attempts to overcome signaling overhead expansion and to define the fundamental basis for designing a tracking area list (TAL). In this context, we differ from other studies by introducing a model that relates the tracking area list to the mobility management entity (MME) which enables more control and adds intelligence to the system. Two MME pooling schemes are investigated namely, centralized and distributed MME schemes. The proposed model is NP-hard; thus, the problem can be simplified with a few assumptions (which do not violate the constraints of the problem) to become a solvable linear problem (LP). Moreover, a low-complexity heuristic algorithm is developed by determining the percentage use of the lists/MME in each cell. The results show that the centralized scheme outperforms the distributed one. Also, the heuristic algorithm offers sub-optimal results when compared to the LP solution.