Computational Intelligence - February 2017 - 29

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Modeling the Tracking
Area Planning Problem
using an evolutionary
Multi-Objective Algorithm

Lei Chen and Hai-Lin Liu
Guangdong University of Technology, Guangzhou, CHINA

Zhun Fan
Guangdong Provincial Key Laboratory of Digital Signal
and Image Processing, Shantou University, Shantou, CHINA

Shengli Xie
Guangdong University of Technology, Guangzhou, CHINA

Erik D. Goodman
BEACON Center for the Study of Evolution in Action,
Michigan State University, USA
Digital Object Identifier 10.1109/MCI.2016.2627669
Date of publication: 6 January 2017

1556-603X/17©2017IEEE

Abstract-When planning the Tracking Areas (TAs) for a
Long Term Evolution (LTE) network, the main concern of
mobile operators is to achieve the minimization of both
location update cost and paging cost. This paper proposes a
new green field TA planning model using multi-objective
optimization with constraints, aiming at finding a better
trade-off between the two conflicting objectives. This new
model integrates the network geographical information,
therefore making it more realistic. Considering the impact of
constraints, we design an evolutionary multi-objective algorithm based on a population decomposition strategy for the
proposed model. Information about infeasible solutions can
be fully utilized by population decomposition and thus the
Corresponding Author: Hai-Lin Liu (e-mail: hlliu@gdut.edu.cn).

FEbruary 2017 | IEEE ComputatIonal IntEllIgEnCE magazInE

29



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