Figure 1.
Table of -neighborhoods of increasing radius around a discrete set of ten equidistant points along the line in , showing how their shape change for different values of p and q.
Figure 1.
Table of -neighborhoods of increasing radius around a discrete set of ten equidistant points along the line in , showing how their shape change for different values of p and q.
Figure 2.
Representation of key regions on the -plane. Corollary 1 shows that is a proper metric in the violet region and Corollary 2 shows that it is an inframetric in the orange and light-gray ones. Numerical evidence suggests that is still a proper metric in the orange regions.
Figure 2.
Representation of key regions on the -plane. Corollary 1 shows that is a proper metric in the violet region and Corollary 2 shows that it is an inframetric in the orange and light-gray ones. Numerical evidence suggests that is still a proper metric in the orange regions.
Figure 3.
(Left) Example of a Pareto front with two archives satisfying condition (i) of Theorem 5 for which . (Right) Example of a Pareto front with two archives satisfying conditions (a’) and (b’) of Remark 3 but for which . In this case partitions of the archives satisfying Theorem 5 (i) do not exist.
Figure 3.
(Left) Example of a Pareto front with two archives satisfying condition (i) of Theorem 5 for which . (Right) Example of a Pareto front with two archives satisfying conditions (a’) and (b’) of Remark 3 but for which . In this case partitions of the archives satisfying Theorem 5 (i) do not exist.
Figure 4.
Example of four approximations of A (black horizontal segment) with (blue piecewise function) for four different values of and fixed .
Figure 4.
Example of four approximations of A (black horizontal segment) with (blue piecewise function) for four different values of and fixed .
Figure 5.
Pareto set (left) and front (right) of MOP (12) for with .
Figure 5.
Pareto set (left) and front (right) of MOP (12) for with .
Figure 6.
Pareto set (left) and front (right) of MOP (12) for with .
Figure 6.
Pareto set (left) and front (right) of MOP (12) for with .
Figure 7.
Left: Approximations A (blue dots) and B (blue polygon line) of the Pareto set (green thick line) of MOP (12) for . Right: corresponding approximations and of the Pareto front, for .
Figure 7.
Left: Approximations A (blue dots) and B (blue polygon line) of the Pareto set (green thick line) of MOP (12) for . Right: corresponding approximations and of the Pareto front, for .
Figure 8.
Left: Approximations A (blue dots) and B (blue polygon line) of the Pareto set (green thick line) of MOP (12) for . Right: corresponding approximations and of the Pareto front, for .
Figure 8.
Left: Approximations A (blue dots) and B (blue polygon line) of the Pareto set (green thick line) of MOP (12) for . Right: corresponding approximations and of the Pareto front, for .
Figure 9.
Left: approximations A (blue dots) corresponding to the 500th generation of the NSGA-II algorithm, and B (blue polygon line) of the Pareto set (green thick line) of MOP (12) for . Right: respective approximations and of the Pareto front for .
Figure 9.
Left: approximations A (blue dots) corresponding to the 500th generation of the NSGA-II algorithm, and B (blue polygon line) of the Pareto set (green thick line) of MOP (12) for . Right: respective approximations and of the Pareto front for .
Figure 10.
Left: approximations A (blue dots) corresponding to the 500th generation of the NSGA-II algorithm, and B (blue polygon line) of the Pareto set (green thick line) of MOP (12) for . Right: respective approximations and of the Pareto front for .
Figure 10.
Left: approximations A (blue dots) corresponding to the 500th generation of the NSGA-II algorithm, and B (blue polygon line) of the Pareto set (green thick line) of MOP (12) for . Right: respective approximations and of the Pareto front for .
Figure 11.
Left: approximations A (blue dots) corresponding to the 500th generation of the MOEA/D algorithm), and B (blue polygon line) of the Pareto set (green thick line) of MOP (12) for . Right: respective approximations and of the Pareto front for .
Figure 11.
Left: approximations A (blue dots) corresponding to the 500th generation of the MOEA/D algorithm), and B (blue polygon line) of the Pareto set (green thick line) of MOP (12) for . Right: respective approximations and of the Pareto front for .
Figure 12.
Left: approximations A (blue dots) corresponding to the 500th generation of the MOEA/D algorithm), and B (blue polygon line) of the Pareto set (green thick line) of MOP (12) for . Right: respective approximations and of the Pareto front for .
Figure 12.
Left: approximations A (blue dots) corresponding to the 500th generation of the MOEA/D algorithm), and B (blue polygon line) of the Pareto set (green thick line) of MOP (12) for . Right: respective approximations and of the Pareto front for .
Figure 13.
Pareto set (left) and front (right) of MOP (14).
Figure 13.
Pareto set (left) and front (right) of MOP (14).
Figure 14.
values for the discrete (black curve) and the continuous archives (blue curve) of NSGA-II for MOP (14).
Figure 14.
values for the discrete (black curve) and the continuous archives (blue curve) of NSGA-II for MOP (14).
Figure 15.
Left: Approximations A (blue dots) and B (blue continuous polygon line) of the Pareto set of MOP (14) in the 300th generation. Right: corresponding approximations and of the Pareto front.
Figure 15.
Left: Approximations A (blue dots) and B (blue continuous polygon line) of the Pareto set of MOP (14) in the 300th generation. Right: corresponding approximations and of the Pareto front.
Figure 16.
Left: Approximations A (blue dots) and B (blue continuous polygon line) of the Pareto set of MOP (14) in the 400th generation. Right: corresponding approximations and of the Pareto front.
Figure 16.
Left: Approximations A (blue dots) and B (blue continuous polygon line) of the Pareto set of MOP (14) in the 400th generation. Right: corresponding approximations and of the Pareto front.
Figure 17.
Left: Approximations A (blue dots) and B (blue continuous polygon line) of the Pareto set of MOP (14) in the 500th generation. Right: corresponding approximations and of the Pareto front.
Figure 17.
Left: Approximations A (blue dots) and B (blue continuous polygon line) of the Pareto set of MOP (14) in the 500th generation. Right: corresponding approximations and of the Pareto front.
Table 1.
values for A and in (10) and (11), for different values of p, q, and , with fixed .
Table 1.
values for A and in (10) and (11), for different values of p, q, and , with fixed .
p | q | | | | |
---|
1 | 1 | | | | |
1 | | | | | |
1 | | | | | |
1 | | | | | |
1 | | | | | |
Table 2.
values for the Pareto set/front approximations for MOP (12).
Table 2.
values for the Pareto set/front approximations for MOP (12).
| p | q | Decision Space | Objective Space |
---|
| Finite Archive | Continuous Archive | Finite Archive | Continuous Archive |
---|
| 1 | 1 | | | | |
1 | | | | | |
1 | | | | | |
1 | | | | | |
| 1 | | | | | |
| 1 | 1 | | | | |
1 | | | | | |
1 | | | | | |
1 | | | | | |
| 1 | | | | | |
Table 3.
Parameter setting for NSGA-II and MOEA/D.
Table 3.
Parameter setting for NSGA-II and MOEA/D.
Algorithm | Parameter | Value |
---|
NSGA-II | Population size | 12 |
Number of generations | 500 |
Crossover probability | 0.8 |
Mutation probability | |
Distribution index for crossover | 20 |
| Distribution index for mutation | 20 |
MOEA/D | Population size | 12 |
# weight vectors | 12 |
Number of generations | 500 |
Crossover probability | 1 |
Mutation probability | |
Distribution index for crossover | 30 |
Distribution index for mutation | 20 |
Aggregation function | Tchebycheff |
Neighborhood size | 3 |
Table 4.
values for the Pareto front approximations for MOP (12) using the NSGA-II archives and with , .
Table 4.
values for the Pareto front approximations for MOP (12) using the NSGA-II archives and with , .
Generation | | |
---|
Finite Archive | Continuous Archive | Finite Archive | Continuous Archive |
---|
50 | | | | |
100 | | | | |
200 | | | | |
250 | | | | |
400 | | | | |
450 | | | | |
460 | | | | |
470 | | | | |
480 | | | | |
490 | | | | |
500 | | | | |
Table 5.
values for the Pareto front approximations for MOP (12) using the MOEA/D archives and with , .
Table 5.
values for the Pareto front approximations for MOP (12) using the MOEA/D archives and with , .
Generation | | |
---|
Finite Archive | Continuous Archive | Finite Archive | Continuous Archive |
---|
50 | | | | |
100 | | | | |
200 | | | | |
250 | | | | |
400 | | | | |
450 | | | | |
460 | | | | |
470 | | | | |
480 | | | | |
490 | | | | |
500 | | | | |
Table 6.
values for the discrete and continuous archives of NSGA-II for MOP (14). The results are averaged over 20 independent runs.
Table 6.
values for the discrete and continuous archives of NSGA-II for MOP (14). The results are averaged over 20 independent runs.
Generation | Continuous Archive | Finite Archive |
---|
20 | | |
40 | | |
60 | | |
80 | | |
100 | | |
120 | | |
140 | | |
160 | | |
180 | | |
200 | | |
220 | | |
240 | | |
260 | | |
280 | | |
300 | | |
320 | | |
340 | | |
360 | | |
380 | | |
400 | | |
420 | | |
440 | | |
460 | | |
480 | | |
500 | | |