Computational Intelligence - February 2017 - 39

It is clear that the proposed algorithm is not very sensitive
to the setting of maximum number of generations since its
HV-metric is very stable after 300 generations of evolution.
Figs. 8-10 plot the distributions of the solutions with the
median HV-metric obtained by M2M versus MOEA/D (not
using the M2M decomposition strategy) for the three networks.
From these figures, we can compare the convergence and diversity of the solutions obtained by M2M and MOEA/D in an intuitive way. Obviously, M2M using the population decomposition

strategy outperforms MOEA/D both in convergence and diversity. It is because of the M2M population strategy that the information of infeasible solutions can be fully utilized to guide the
population search. Since the TA planning problem has a lot of
complex constraints, some infeasible solutions can be very crucial
during the evolutionary process. In the M2M framework, the
selection operator is conduced independently in each subpopulation, and those infeasible but crucial solutions are more likely to
survive. The algorithm without the M2M population strategy

TABle 5 The Location Update Cost (LUC), Paging Cost (PC) and Weight Sum Cost (WSC) of network 2 for 10 groups of test parameters.
NeTwOrk 2

MulTi-OBjecTive MOdel

SiNgle-OBjecTive MOdel

grOuP

luc

Pc

wSc

luc

Pc

wSc

1

5994

26235

86175

5994

26235

86175

2

6372

21159

84879

7648

18019

94499

3

6258

24310

86890

9086

17267

108127

4

6576

24512

90272

7566

19440

95100

5

6816

23519

91679

6928

23736

93016

6

6410

23014

87114

6992

25375

95295

7

7212

21704

93824

6934

21210

90550

8

5762

26430

84050

7868

18321

97001

9

7090

21038

91938

8338

21322

104702

10

7346

21217

94677

10080

15132

115932

TABle 6 The Location Update Cost (LUC), Paging Cost (PC) and Weight Sum Cost (WSC) of network 3 for 10 groups of test parameters.
NeTwOrk 3

MulTi-OBjecTive MOdel

SiNgle-OBjecTive MOdel

grOuP

luc

Pc

wSc

luc

Pc

wSc

1

16148

70297

231777

18210

57814

239914

2

15274

50119

202859

18738

55787

243167

3

14238

54597

196977

17596

54089

230049

4

14490

60501

205401

19330

60836

254136

5

15114

54757

205897

18288

60033

242913

6

13762

50298

187918

18576

60557

246317

7

13872

57336

196056

18572

54191

239911

8

15274

50119

202859

18378

60369

244149

9

14238

54597

196977

17776

61728

239488

10

14490

60501

205401

17446

63466

237926

TABle 7 Best, worst, median, mean, and standard deviation of HV-metric values obtained by M2M and MOEA/D
in 15 independent runs for each network.
neTwOrk

AlgOrIThM

BeST

wOrST

MedIAn

MeAn

STd

1

M2M

22.0228

21.3033

21.69178

21.68115

0.194377

MOeA/d

21.6442

21.0631

21.33346

21.33535

0.210806

M2M

21.6862

21.1803

21.41088

21.39275

0.188406

MOeA/d

21.3409

20.5926

20.93512

20.9217

0.272798

M2M

18.4156

17.7834

18.10996

18.14175

0.194861

MOeA/d

17.6228

17.0018

17.32225

17.3455

0.204509

2

3

FEbruary 2017 | IEEE ComputatIonal IntEllIgEnCE magazInE

39



Table of Contents for the Digital Edition of Computational Intelligence - February 2017

Computational Intelligence - February 2017 - Cover1
Computational Intelligence - February 2017 - Cover2
Computational Intelligence - February 2017 - 1
Computational Intelligence - February 2017 - 2
Computational Intelligence - February 2017 - 3
Computational Intelligence - February 2017 - 4
Computational Intelligence - February 2017 - 5
Computational Intelligence - February 2017 - 6
Computational Intelligence - February 2017 - 7
Computational Intelligence - February 2017 - 8
Computational Intelligence - February 2017 - 9
Computational Intelligence - February 2017 - 10
Computational Intelligence - February 2017 - 11
Computational Intelligence - February 2017 - 12
Computational Intelligence - February 2017 - 13
Computational Intelligence - February 2017 - 14
Computational Intelligence - February 2017 - 15
Computational Intelligence - February 2017 - 16
Computational Intelligence - February 2017 - 17
Computational Intelligence - February 2017 - 18
Computational Intelligence - February 2017 - 19
Computational Intelligence - February 2017 - 20
Computational Intelligence - February 2017 - 21
Computational Intelligence - February 2017 - 22
Computational Intelligence - February 2017 - 23
Computational Intelligence - February 2017 - 24
Computational Intelligence - February 2017 - 25
Computational Intelligence - February 2017 - 26
Computational Intelligence - February 2017 - 27
Computational Intelligence - February 2017 - 28
Computational Intelligence - February 2017 - 29
Computational Intelligence - February 2017 - 30
Computational Intelligence - February 2017 - 31
Computational Intelligence - February 2017 - 32
Computational Intelligence - February 2017 - 33
Computational Intelligence - February 2017 - 34
Computational Intelligence - February 2017 - 35
Computational Intelligence - February 2017 - 36
Computational Intelligence - February 2017 - 37
Computational Intelligence - February 2017 - 38
Computational Intelligence - February 2017 - 39
Computational Intelligence - February 2017 - 40
Computational Intelligence - February 2017 - 41
Computational Intelligence - February 2017 - 42
Computational Intelligence - February 2017 - 43
Computational Intelligence - February 2017 - 44
Computational Intelligence - February 2017 - 45
Computational Intelligence - February 2017 - 46
Computational Intelligence - February 2017 - 47
Computational Intelligence - February 2017 - 48
Computational Intelligence - February 2017 - 49
Computational Intelligence - February 2017 - 50
Computational Intelligence - February 2017 - 51
Computational Intelligence - February 2017 - 52
Computational Intelligence - February 2017 - 53
Computational Intelligence - February 2017 - 54
Computational Intelligence - February 2017 - 55
Computational Intelligence - February 2017 - 56
Computational Intelligence - February 2017 - Cover3
Computational Intelligence - February 2017 - Cover4
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202311
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202308
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202305
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202302
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202211
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202208
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202205
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202202
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202111
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202108
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202105
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202102
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202011
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202008
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202005
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202002
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201911
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201908
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201905
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201902
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201811
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201808
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201805
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201802
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter17
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall17
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer17
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring17
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter16
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall16
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer16
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring16
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter15
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall15
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer15
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring15
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter14
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall14
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer14
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring14
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter13
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall13
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer13
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring13
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter12
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall12
https://www.nxtbookmedia.com