Fig 1.
The flowchart of ETBBPSO.
Table 1.
Experimental functions, the CEC 2014 benchmark functions, the search range for each function is (-100,100), the dimension is 100.
Table 2.
Experimental results, CE of PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO for f1−f15.
Mean is the mean valut from 31 independent runs, STD is the standard deviation of the 31 runs, Rank is the rank of 6 algorithms.
Table 3.
Experimental Results, CE of PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO for f16−f30.
Mean is the mean valut from 31 independent runs, STD is the standard deviation of the 31 runs, Rank is the rank of 6 algorithms. Alvrage rank point is at the bottom of the table.
Table 4.
Parameters of the CEC2020 test.
Fig 2.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f1, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 3.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f2, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 4.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f3, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 5.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f4, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 6.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f5, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 7.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f6, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 8.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f7, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 9.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f8, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 10.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f9, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 11.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f10, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 12.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f11, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 13.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f12, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 14.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f13, (a) iteration 0-6000, (b) iteration 6000-10000, the unit is 100 iteration.
Fig 15.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f14, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 16.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f15, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 17.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f16, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 18.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f17, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 19.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO,f18, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 20.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f19, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 21.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f20, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 22.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f21, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 23.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f22, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 24.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f23, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 25.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f24, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 26.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f25, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 27.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f26, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 28.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f27, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 29.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f28, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 30.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f29, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Fig 31.
Comparison of convergence speed between PSO, PBBPSO, DA-BBPSO, DLS-BBPSO, FBBPSO and ETBBPSO, f30, (a) iteration 0-6000, (b) iteration 6000-10000 the unit is 100 iteration.
Table 5.
Experimental Results with CEC2020, CEs of BBPSO and ETBBPSO.
Mean is the mean valut from 31 independent runs, STD is the standard deviation of the 31 runs.