Research Article
An Elitist Transposon Quantum-Based Particle Swarm Optimization Algorithm for Economic Dispatch Problems
Table 5
Results obtained by optimization methods (case I).
| | Methods | Best cost ($/h) | Worst cost ($/h) | Mean cost ($/h) | FEs | CPU time (s) |
| | PSO [11] | 32858.00 | 33331.00 | 33105.00 | 20,000 | / | | GA [11] | 33113.00 | 33337.00 | 33228.00 | 20,000 | / | | SA-PSO [12] | 32708.00 | 32789.00 | 32732.00 | 20,000 | / | | IPSO [13] | 32,709 | — | 32784.5 | 10,000 | / | | DSPSO-TSA [14] | 32715.06 | 32730.39 | 32724.63 | 6000 | / | | MTS [22] | 32716.87 | 32796.13 | 32767.4 | 100,000 | / | | IA_EDP [7] | 32698.20 | 32823.78 | 32750.22 | 20,000 | / | | QPSO [39] | 33014.21 | 33342.30 | 33148.77 | 6000 | / | | QPSO-DM(1) [39] | 32970.85 | 33406.27 | 33163.26 | 6000 | / | | QPSO-DM(2) [39] | 32927.93 | 33353.23 | 33156.34 | 6000 | / | | QPSO-EDP(1) | 32707.99 | 32718.39 | 32712.02 | 6000 | 4.27 | | QPSO-EDP(2) | 32710.14 | 32719.27 | 32716.94 | 6000 | 6.35 | | DEB-QPSO | 32701.16 | 32701.18 | 32701.17 | 6000 | 4.68 |
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In the case of IA_EDP, power balance constraint is not satisfied. |
