Computational Intelligence - May 2014 - 67
Table 4 Simulation results on the ba scale-free graphs. The values in each row are the average on 30 randomly generated interference
graphs, the standard difference of the 30 values of the total cost is given in the parentheses.
TOTal COST
NuMber OF SPilleD NODeS
TiMe (s)
n
m
mo
b
OCH
COMa
Hea
OCH
COMa
Hea
OCH
COMa
Hea
100
12
15
0.06
795.20
340.13
370.8
25.27
15.43
16.00
0.03
851.21
586.83
(147.61)
(27.82)
(28.63)
279.10
110.77
137.73
9.67
5.43
6.43
0.03
213.41
164.07
(71.17)
(25.40)
(19.09)
1109.63
478.90
536.10
35.30
22.13
22.73
0.03
896.53
752.53
(119.59)
(34.45)
(34.33)
593.63
218.40
252.60
18.90
11.83
11.90
0.03
289.00
198.43
(107.99)
(21.61)
(16.09)
1267.47
404.23
494.13
44.67
32.07
32.53
0.07
1439.98
908.59
(123.55)
(34.80)
(37.56)
383.27
96.53
141.23
13.63
12.80
13.83
0.05
709.91
521.11
(97.89)
(18.66)
(21.46)
2012.17
762.43
898.70
71.07
50.60
51.63
0.07
2513.62
969.67
(150.17)
(34.73)
(35.43)
1096.17
296.43
375.37
39.21
27.77
29.07
0.05
1218.35
790.67
(137.91)
(21.54)
(26.58)
0.08
15
20
0.06
0.08
200
30
40
0.06
0.08
40
50
0.06
0.08
COMA v = 18.66
10
HEA
v = 21.46
OCH
v = 97.89
5
0
0
200
400
600
LFR, n = 200, = 40, kmax = 100, n = 0.6, b = 0.06
Number of Times Appear
Number of Times Appear
BA Graphs, n = 200, m = 30, mo = 40, b = 0.08
15
800
15
COMA v = 33.04
10
HEA
v = 41.80
OCH
v = 141.43
5
0
0
200
Total Cost
(a)
400
600
800
1000
Total Cost
(b)
Figure 6 Distributions of the 30 results of the total cost for the three algorithms. (a) BA scale-free graphs. (b) LFR modular graphs.
graphs. But in scale-free and modular
graphs, it is usually that Fitness M (R i)
< Fitness S (R i) . Thus the Fitness (R i)
calculated by (3) is evidently smaller
than that calculated by (1) in scale-free
and modular graphs.
IV. Conclusion
The node-weighted resource allocation
problem formulated in this paper is a
generalization of the k -coloring prob-
lem. By appropriately utilizing the cost
infor mation, the cost-or iented
memetic algorithm (COMA) for the
resource allocation problem is provided.
The COMA has two main contributions: one is the metric-based technique to decode a chromosome and
the other is the cost-oriented crossover
operator (COPX). The metric-based
technique is a combination of two
types of information: conflict (edge)
and cost (weight), which can produce
smaller value of the fitness in general
than using any one of the two types of
information. The metric-based technique can reduce both the total cost
and the number of spilled nodes but
requires more runtime. The COPX is a
modification of the CFPX. The difference between the two operators is that
the COPX tends to reduce the total
cost whereas the CFPX tends to reduce
may 2014 | IEEE ComputatIonal IntEllIgEnCE magazInE
67
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