Research Article

A Modified Bat Algorithm with Conjugate Gradient Method for Global Optimization

Table 3

Comparison between CG-BAT and classical algorithm on benchmark functions (F11∼F20).

CG-BATBAFACSPSO

F11Best7.536E + 012.799E + 001.414E + 021.337E + 022.904E − 05
Median1.561E + 022.103E + 011.879E + 022.190E + 029.745E − 03
Worst2.506E + 020.334E + 022.352E + 023.009E + 024.370E − 03
Mean1.515E + 023.629E + 011.937E + 022.214E + 026.006E − 03
SD4.105E + 011.971E + 012.433E + 014.094E + 015.407E − 03

F12Best9.448E − 031.323E + 002.650E + 011.059E + 023.343E + 02
Median1.528E − 022.187E + 016.164E + 012.200E + 024.437E + 02
Worst3.044E − 019.385E + 021.438E + 026.159E + 026.492E + 02
Mean1.911E − 011.181E + 026.790E + 012.611E + 021.304E + 03
SD4.917E − 012.293E + 022.559E + 011.384E + 027.193E + 02

F13Best2.094E − 009.637E + 011.259E + 011.673E + 022.121E + 02
Median1.470E − 038.037E + 021.123E + 021.444E + 011.484E + 02
Worst9.5017E − 023.847E + 021.011E + 021.333E + 021.889E + 02
Mean1.495E − 018.475E + 001.121E + 011.455E + 012.452E + 02
SD3.135E + 006.847E − 017.085E − 017.923E − 010.937E + 02

F14Best1.344E + 008.475E + 002.073E + 031.778E + 021.433E + 01
Median2.815E + 014.501E + 014.076E + 033.536E + 022.950E + 01
Worst1.918E + 027.523E + 029.651E + 037.081E + 026.164E + 01
Mean4.898E + 011.695E + 024.532E + 033.554E + 021.438E + 02
SD5.028E + 012.220E + 021.861E + 031.311E + 026.790E + 01

F15Best4.499E + 011.382E + 041.283E + 051.542E + 080.559E + 08
Median3.283E + 024.133E + 052.388E + 053.709E + 080.259E + 09
Worst2.518E + 031.247E + 073.528E + 056.179E + 081.123E + 10
Mean4.926E + 021.929E + 062.392E + 053.760E + 081.011E + 02
SD5.304E + 023.115E + 066.522E + 041.192E + 081.121E + 01

F16Best3.462E − 026.731E + 001.271E + 011.112E + 013.085E + 01
Median0.239E + 011.505E + 011.522E + 011.404E + 018.073E + 03
Worst2.046E + 012.832E + 021.912E + 021.834E + 029.076E + 03
Mean3.716E + 001.647E + 011.528E + 011.452E + 019.651E + 03
SD4.409E + 005.854E + 001.682E + 001.746E + 004.532E + 03

F17Best2.719E + 023.067E + 011.483E + 012.157E + 011.551E + 03
Median3.085E + 023.181E + 012.232E + 012.788E + 011.743E + 05
Worst3.320E + 023.270E + 012.805E + 012.988E + 012.388E + 06
Mean3.053E + 013.178E + 012.276E + 012.718E + 013.528E + 05
SD1.668E + 004.720E − 013.374E + 002.463E + 002.392E + 05

F18Best1.131E + 021.637E + 022.948E + 022.564E + 026.522E + 04
Median1.979E + 022.550E + 023.687E + 023.163E + 021.271E + 11
Worst2.686E + 024.179E + 024.154E + 023.596E + 021.522E + 11
Mean1.959E + 022.651E + 023.627E + 023.168E + 021.912E + 02
SD3.767E + 016.899E + 013.236E + 012.533E + 011.528E + 01
F19Best5.054E − 015.082E − 012.426E + 011.337E + 021.682E + 00
Median3.328E − 005.697E + 014.450E + 012.190E + 061.993E + 01
Worst3.357E − 007.542E + 018.646E + 013.377E + 032.762E + 01
Mean2.417E − 005.172E + 014.591E + 015.082E + 062.805E + 01
SD4.826E − 011.981E + 031.265E + 018.308E + 047.542E + 01

F20Best2.861E − 005.453E + 005.729E + 005.193E + 015.1842E + 01
Median4.319E − 005.964E + 006.177E + 001.241E + 027.981E + 03
Worst5.766E − 006.693E + 006.674E + 002.769E + 039.453E + 00
Mean1.262E − 006.019E + 006.187E + 003.347E + 005.554E + 00
SD7.905E − 013.268E − 012.475E − 013.761E + 006.693E + 00