Research Article
Solving Interval Quadratic Programming Problems by Using the Numerical Method and Swarm Algorithms
Table 5
The statistical results of SAs over the 30 runs.
| | Algorithm | CPU time(s) | Mean | SD | Worst | Best |
| Problem 1 | Range of | [1.025, 74] | PSO | 5.45 | 1.6783 | 0.0419 | 1.7024 | 1.6209 | FA | 4.56 | 1.5337 | 0.0065 | 1.5379 | 1.5252 | CPSO | 3.76E−002 | 1.0250 | 0 | 1.0250 | 1.0250 | CFA | 2.95E−002 | 1.0250 | 0 | 1.0250 | 1.0250 |
| Problem 2 | Range of | [−3.5, −0.75] | PSO | 12.05 | −3.2244 | 0.0458 | −3.1846 | −3.2759 | FA | 7.96 | −3.3230 | 0.0066 | −3.3257 | −3.3355 | CPSO | 2.54E−002 | −3.4999 | 0 | −3.4999 | −3.4999 | CFA | 1.51E−002 | −3.5 | 0 | −3.5 | −3.5 |
| Problem 3 | Range of | [−3.4922, 0.5217] | PSO | 22.45 | −1.8795 | 0.0304 | −1.8750 | −1.9297 | FA | 10.38 | −3.1498 | 0.0487 | −3.0907 | −3.1872 | CPSO | 9.41E−002 | 2.7037 | 0.0013 | −2.7005 | −2.7046 | CFA | 8.95E−002 | −3.4922 | 0 | −3.4922 | −3.4922 |
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