In this paper we research the location management, a vital task that controls the subscribers’ mobility in the mobile communication networks. This management task defines a multiobjective optimization problem with two objective functions: minimize the number of location updates and minimize the paging overhead. In this work, the first objective function is described following the Location Areas strategy (because it is widely used in current mobile networks) and the second one is expressed following different paging procedures. Furthermore, the different location management strategies studied in this work are optimized with our versions of two well-known multiobjective evolutionary algorithms (the Non-dominated Sorting Genetic Algorithm II and the Strength Pareto Evolutionary Algorithm 2). This study is a novel contribution of our research which will allow us to select the most suitable configuration of LA-PA (Location Areas with a specific paging procedure) depending on the real state of the signaling network. Experimental results also show that our proposals are very competitive because they outperform the results obtained by other optimization techniques proposed in the literature. 
On the use of multiobjective optimization for solving the Location Areas strategy with different paging procedures in a realistic mobile network