Improved ant colony optimization algorithms for continuous ... - CoDE
Improved ant colony optimization algorithms for continuous ... - CoDE
Improved ant colony optimization algorithms for continuous ... - CoDE
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10 Ant Colony Optimization<br />
of Sep-ACOR. In the following Chapter 3, an improved ACO algorithm is<br />
presented.<br />
ellipsoid, threshold= 1e−10 rotatedellipsoid, threshold= 1e−10<br />
Numbers of Evaluations<br />
Numbers of Evaluations<br />
Numbers of Evaluations<br />
50000<br />
40000<br />
30000<br />
20000<br />
10000<br />
0<br />
6000<br />
5000<br />
4000<br />
3000<br />
2000<br />
1000<br />
10000<br />
8000<br />
6000<br />
4000<br />
2000<br />
0<br />
q=1e−04<br />
m<strong>ant</strong>=2<br />
k=50<br />
xi=0.85<br />
ACOrC−d2<br />
ACOrC−d2<br />
ACOrR−d2<br />
ACOrC−d6<br />
ACOrR−d6<br />
ACOrC−d10<br />
ACOrR−d10<br />
ACOrC−d15<br />
tablet, threshold= 1e−10<br />
q=1e−04<br />
m<strong>ant</strong>=2<br />
k=50<br />
xi=0.85<br />
ACOrC−d2<br />
ACOrR−d2<br />
ACOrC−d6<br />
ACOrR−d6<br />
ACOrC−d10<br />
ACOrR−d10<br />
ACOrC−d15<br />
cigar, threshold= 1e−10<br />
q=1e−04<br />
m<strong>ant</strong>=2<br />
k=50<br />
xi=0.85<br />
ACOrR−d2<br />
ACOrC−d6<br />
ACOrR−d6<br />
ACOrC−d10<br />
ACOrR−d10<br />
ACOrC−d15<br />
ACOrR−d15<br />
ACOrR−d15<br />
ACOrR−d15<br />
Numbers of Evaluations<br />
Numbers of Evaluations<br />
Numbers of Evaluations<br />
60000<br />
50000<br />
40000<br />
30000<br />
20000<br />
10000<br />
0<br />
6000<br />
5000<br />
4000<br />
3000<br />
2000<br />
1000<br />
10000<br />
8000<br />
6000<br />
4000<br />
2000<br />
0<br />
q=1e−04<br />
m<strong>ant</strong>=2<br />
k=50<br />
xi=0.85<br />
ACOrC−d2<br />
ACOrC−d2<br />
ACOrR−d2<br />
ACOrR−d2<br />
ACOrC−d6<br />
ACOrC−d6<br />
ACOrR−d6<br />
ACOrR−d6<br />
ACOrC−d10<br />
ACOrC−d10<br />
ACOrR−d10<br />
ACOrR−d10<br />
ACOrC−d15<br />
ACOrC−d15<br />
ACOrR−d15<br />
rotatedtablet, threshold= 1e−10<br />
q=1e−04<br />
m<strong>ant</strong>=2<br />
k=50<br />
xi=0.85<br />
ACOrC−d2<br />
ACOrR−d2<br />
ACOrC−d6<br />
ACOrR−d6<br />
ACOrC−d10<br />
ACOrR−d10<br />
ACOrC−d15<br />
ACOrR−d15<br />
rotatedcigar, threshold= 1e−10<br />
q=1e−04<br />
m<strong>ant</strong>=2<br />
k=50<br />
xi=0.85<br />
Figure 2.1: The box-plot comparison between C++ and R implementation<br />
of ACOR on different dimensionality. ACOrC is the C++ implementation<br />
of ACOR and ACOrR is the original R implementation. The left box plots<br />
are shown the numbers of function evaluations when achieving the threshold<br />
of solution quality in non-rotated functions, on the right box-plots those of<br />
rotated functions. We set the threshold of solution quality to 1e−10. The<br />
adopted parameter configurations of ACOR are shown in the legends.<br />
ACOrR−d15