Paper Info
Title
Studying the Reporting Cells Planning with the Non-dominated Sorting Genetic Algorithm II.
Abstract
This manuscript addresses a vital task in any Public Land Mobile Network, the mobile location management. This management task is tackled following the Reporting Cells strategy. Basically, the Reporting Cells planning consists in selecting a subset of network cells as Reporting Cells with the aim of controlling the subscribers' movement and minimizing the signaling traffic. In previous works, the Reporting Cells Planning Problem was optimized by using single-objective metaheuristics, in which the two objective functions were linearly combined. This technique simplifies the optimization problem but has got several drawbacks. In this work, with the aim of avoiding such drawbacks, we have adapted a well-known multiobjective metaheuristic: the Non-dominated Sorting Genetic Algorithm II (NSGAII). Furthermore, a multiobjective approach obtains a wide range of solutions (each one related to a specific trade-off between objectives), and hence, it gives the possibility of selecting the solution that best adjusts to the real state of the signaling network. The quality of our proposal is checked by means of an experimental study, where we demonstrate that our version of NSGAII outperforms other algorithms published in the literature.
Year
DOI
Venue
2014
10.1007/978-3-662-45523-4_6
Lecture Notes in Computer Science
Keywords
Field
DocType
Reporting Cells Planning Problem,Mobile location management,Multiobjective optimization,Non-dominated Sorting Genetic Algorithm II
Data mining,Mobile location,Computer science,Signaling network,Public land mobile network,Sorting,Multi-objective optimization,Artificial intelligence,Optimization problem,Genetic algorithm,Metaheuristic
Conference
Volume
ISSN
Citations 
8602
0302-9743
1
PageRank 
References 
Authors
0.35
7
3
Name
Order
Citations
PageRank
Víctor Berrocal-Plaza1266.57
Miguel A. Vega-Rodríguez2741113.05
Juan Manuel Sánchez-Pérez327830.84