Research Article

A Novel Teaching-Learning-Based Optimization with Error Correction and Cauchy Distribution for Path Planning of Unmanned Air Vehicle

Table 3

Results of ten algorithms over 25 independent times on 6 test functions of 30 dimensions with 300,000 FES.

FunctionResultPSODEABCCSGSOWCADSABSAISAECTLBO

F13.15E + 03−4.85E − 14−8.19E + 03−2.48E − 00−8.83E + 02−4.81E − 01−1.38E + 03−1.08E + 02−2.22E − 04−9.60E − 15
SD4.22E + 031.16E − 131.82E + 031.06E − 001.71E + 024.00E − 014.88E + 024.82E + 016.16E − 041.48E − 10

F22.50E + 07−9.23E + 05−9.01E + 06−3.36E + 06−2.17E + 06−1.74E + 06−1.38E + 07−1.88E + 06−1.18E + 07−8.73E + 05
SD2.53E + 074.56E + 051.95E + 067.40E + 055.19E + 056.20E + 055.67E + 067.10E + 055.36E + 063.30E + 05

F32.09E + 01−2.10E + 01−2.03E + 01≈2.09E + 01−2.03E + 01≈2.04E + 01≈2.09E + 01−2.09E − 01−2.03E + 01≈2.03 E + 01
SD6.47E − 024.20E − 024.60E − 026.97E − 021.08E − 016.57E − 025.36E − 025.52E − 021.17E − 015.39E − 02

F47.51E + 01−1.90E + 01−0+6.09E + 01−7.76E − 00+4.90E + 01−0+3.61E − 14+1.17E + 02+1.23E + 01
SD3.28E + 014.28E − 0007.96E − 003.00E − 001.55E + 0101.14E − 132.76E + 012.04E + 01

F51.25E + 02−1.28E + 02−3.39E + 02−1.39E + 02−3.21E + 02−1.57E + 02−9.54E + 02−8.34E + 01+1.53E + 0241.19E + 02
SD3.31E + 016.77E + 014.87E + 011.77E + 017.18E + 014.05E + 011.18E + 011.55E + 0197E + 011.53E + 01

F63.36E − 00≈2.94E − 00−1.13E − 00+6.74E − 00−2.10E − 00+9.86E − 00−1.85E − 00+1.75E − 00+4.42E − 00−3.36E + 00
SD7.40E − 017.24E − 019.39E − 017.47E − 014.53E − 012.02E − 008.90E − 011.29E − 001.15E − 006.28E − 01

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“−,” “+,” and “≈”denote that the performance of the corresponding algorithm is significantly worse than, significantly better than, and similar to that of ECTLBO, respectively.